System and methods for location-based medical rendering

Abstract

To provide a system and methods for location-based medical rendering.SOLUTION: A system and methods of location-based medical rendering that automatically generate improved renderings, such as 4D ICE imagery, of anatomical structures are disclosed. According to some embodiments, the methods include: obtaining images and position data from a catheter having a distal tip furnished with an ultrasound imaging device and a position sensor; processing the position data of the ultrasound imaging device to determine a volumetric field of regard (FOR) of the imaging device in a patient's body; obtaining a model of at least a portion of a body anatomy present within the FOR; and utilizing the model to optionally (i) adjust capturing parameters of the ultrasound imaging device based on the model to optimize capturing of a body anatomy of interest by the ultrasound imaging device with diminished appearance of its surrounding tissues, and / or (ii) crop images grabbed from the FOR of the imaging device to the body anatomy of interest.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates generally to imaging and medical visualization methods, and more particularly to visualization of anatomical structures acquired by intrabody medical imaging devices such as ultrasound probes. [Background technology]

[0002] Three-dimensional (3D) and four-dimensional (4D) images (i.e., 3D video sequences) of anatomical structures, such as ultrasound images / videos of the heart, are useful in many catheter-based diagnostic and therapeutic applications. Real-time imaging improves physician performance, allowing even relatively inexperienced physicians to perform complex surgical procedures more easily. 3D imaging also reduces the time required to perform some surgical procedures.

[0003] Some systems use hybrid catheters that incorporate position sensing. For example, U.S. Patent No. 6,690,963 to Ben-Haim et al., assigned to the assignee of the present invention and whose disclosure is incorporated herein by reference, describes a positioning system for determining the position or orientation of an invasive medical instrument.

[0004] Non-contact imaging of the endocardium can use a catheter equipped with acoustic transducers. For example, U.S. Patent No. 6,716,166 to Govari and U.S. Patent No. 6,773,402 to Govari et al., both of which are assigned to the assignee of the present invention and whose disclosures are incorporated herein by reference, describe a system for 3D mapping and geometric reconstruction of body cavities, particularly the heart. This system uses a cardiac catheter equipped with multiple acoustic transducers. The transducers emit ultrasound waves that are reflected off the surface of the cavity and received again by the transducers. The distance from each transducer to a specific point or region on the surface opposite the transducer is measured, and the three-dimensional shape of the surface is reconstructed by combining these distance measurements. The catheter also includes a position sensor that is used to determine the position or orientation coordinates of the catheter within the heart.

[0005] Typically, such systems provide an "endoscopic view," in which the reconstructed image is presented as it would appear if viewed through a catheter or other probe. For example, U.S. Patent No. 6,556,695 to Packer et al., the disclosure of which is incorporated herein by reference, describes a method for generating high-resolution, real-time images of the heart. During medical procedures such as endocardial physiology mapping and ablation, real-time images are generated by an ultrasound transducer inserted into the heart. A high-resolution cardiac model is registered with the acquired real-time images and used to generate dynamic, high-resolution images for display during the procedure. Different portions of the anatomy can be viewed by moving the distal tip of the catheter to "point" the acoustic transducer toward the structure of interest. When other portions of the anatomy are examined without moving the catheter, a joystick can be used to scan away from the ultrasound transducer's field of view. Orientation within the anatomy (e.g., a heart chamber) is maintained using navigation icons, such as those described in U.S. Patent No. 6,049,622 to Robb et al., the disclosure of which is also incorporated herein by reference.

[0006] Similarly, U.S. Patent No. 6,203,497 to Dekel et al. (the disclosure of which is also incorporated herein by reference) describes a system and method for visualizing internal images of an anatomical body. Internal images of the body are acquired by an ultrasound imaging transducer that is tracked in a reference frame by a spatial determiner. The position of the image in the reference frame is determined by calibrating the ultrasound imaging transducer to generate a vector position of the image relative to a fixed point on the transducer. This vector position can then be added to the position and orientation of the fixed point of the transducer in the reference frame determined by the spatial determiner. The position and orientation of a medical instrument used on the patient are also tracked in the reference frame by the spatial determiner. This information is used to generate processed images from views that are spatially related to the position of the instrument.

[0007] U.S. Patent No. 7,020,512 (Ritter et al.), the disclosure of which is incorporated herein by reference, describes a method for locating a medical device inside a patient's body. AC magnetic signals of different frequencies are transmitted between a point at a known location outside the patient's body and a point on the medical device inside the patient's body. The transmitted AC magnetic signals are then processed to determine the location of the point on the medical device, and therefore the location of the medical device. This processing includes correcting for the effects of metal in the vicinity by using the transmitted and received signals at different frequencies.

[0008] U.S. Patent No. 7,020,512 also describes an alternative embodiment in which a reference catheter is provided within the patient's body and the medical device is localized relative to the reference catheter. The use of a signal including at least two frequencies may or may not be used in this relative localization embodiment, but is typically used to localize at least the reference catheter.

[0009] U.S. Patent No. 10,299,753 to Govari et al., assigned to the assignee of the present invention and whose disclosure is incorporated herein by reference, discloses a method for imaging an anatomical structure on a display, including obtaining an initial spatial representation of the anatomical structure and positioning an instrument proximate the anatomical structure. The method further includes determining a position of the instrument and generating an image of a portion of the anatomical structure in response to the position. The method includes adding the image to the initial spatial representation and displaying the combined spatial representation. [Brief explanation of the drawings]

[0010] In order to better understand the subject matter disclosed herein and to illustrate how it may be carried out in practice, embodiments will now be described, by way of non-limiting example only, with reference to the accompanying drawings, in which: [Figure 1] 1 is a schematic, pictorial illustration of a catheter-based ultrasound imaging system using a catheter having a distal tip assembly comprising a 2D ultrasound array and a location sensor, in accordance with an embodiment of the present invention; [Figure 2A] 2A and 2B show medical images processed by the techniques of the present invention, where FIG. 2A shows an initial / pre-processed image of an anatomical structure, FIG. 2B is an isolated image of an anatomical structure captured according to the techniques of the present invention, and FIG. 2C shows a cropped image of an anatomical structure generated by the techniques of the present invention. [Figure 2B] 2A and 2B show medical images processed by the techniques of the present invention, where FIG. 2A shows an initial / pre-processed image of an anatomical structure, FIG. 2B is an isolated image of an anatomical structure captured according to the techniques of the present invention, and FIG. 2C shows a cropped image of an anatomical structure generated by the techniques of the present invention. [Figure 2C] 2A and 2B show medical images processed by the techniques of the present invention, where FIG. 2A shows an initial / pre-processed image of an anatomical structure, FIG. 2B is an isolated image of an anatomical structure captured according to the techniques of the present invention, and FIG. 2C shows a cropped image of an anatomical structure generated by the techniques of the present invention. [Figure 3A]1A and 1B are a block diagram and a flowchart, respectively, presenting a system and a method for acquiring isolated medical images of a subject's body anatomy, according to embodiments of the present invention; [Figure 3B] 1A and 1B are a block diagram and a flowchart, respectively, presenting a system and a method for acquiring isolated medical images of a subject's body anatomy, according to embodiments of the present invention; [Figure 3C] 10A-10C schematically illustrate the adaptation of a capture area of ​​an imaging device of a catheter to a region of interest where a body anatomical structure is present, according to an embodiment of the present invention; [Figure 4A] 1A and 1B are a block diagram and a flowchart, respectively, presenting a system and method for cropping a medical image of a subject's body anatomy, according to an embodiment of the present invention; [Figure 4B] 1A and 1B are a block diagram and a flowchart, respectively, presenting a system and method for cropping a medical image of a subject's body anatomy, according to an embodiment of the present invention;

[0011] The same reference numbers are used in the following figures for elements / acts in the figures that have similar configurations and / or functions. DETAILED DESCRIPTION OF THE INVENTION

[0012] Images of anatomical structures such as the heart, particularly high-dimensional images such as three- or four-dimensional (3-D or 4-D, collectively also referred to herein as nD images), typically contain a large amount of visual information, and therefore often make it difficult for a viewer to distinguish features of interest within the image from the surrounding background. The present invention addresses this problem and facilitates the viewing of nD images that present a particular anatomical structure of a subject, or a portion thereof, substantially isolated / removed from surrounding body tissue, fluid, or other anatomical structures. To this end, embodiments of the present invention provide systems and methods for capturing an isolated image of the anatomical structure of a subject, substantially removed from the surrounding background, and / or for processing a captured image in which the anatomical structure of the subject is present, to generate therefrom a cropped image of the anatomical structure with its surroundings removed. Some embodiments of the present invention facilitate an observer, typically a system operator or physician, to select an anatomical structure or portion thereof for which an image is to be generated, and capture an isolated image of that using a corresponding model of the anatomical structure and / or crop that image, such that the isolated or cropped image presents the anatomical structure (also referred to herein as body anatomy) or portion(s) thereof with or without reduced perimeter.

[0013] Embodiments of the present invention may be used to view images of anatomical structures, including cavities, as well as different anatomical structures or portions thereof, which will be assumed below, by way of example, to include the patient's heart or a portion thereof.

[0014] 1 is a schematic, pictorial illustration of a catheter-based imaging system 20. In accordance with an embodiment of the present invention, system 20 utilizes a catheter 21 having a distal tip assembly 40 that includes an imaging device 50 and a position sensor 52 that can provide data indicative of the position and orientation of imaging device 50.

[0015] Specifically, position sensor 52 is configured to output a signal indicative of the position and orientation of imaging device 50 within the body (e.g., within an organ thereof) of patient 28. Imaging device 50 may be configured and operable to implement any one of a variety of medical imaging techniques, for example, ultrasound imaging.

[0016] 1 , a distal tip assembly 40 of the catheter 21 is located at the distal end of a shaft 22 of the catheter 21. The catheter 21 is shown inserted through a sheath 23 and into a heart 26 of a patient 28 lying on an operating table 29. The proximal end of the catheter 21 is connected to a control console 24. In the particular embodiment described herein, the catheter 21 is used for ultrasound-based diagnostic purposes; however, generally, the catheter may implement other medical imaging techniques in addition to or instead of ultrasound imaging, or may be further adapted to perform additional therapeutic operations, such as electrical sensing and / or ablation of tissue within the heart 26, for example, using one or more distal tip electrodes 56. A physician 30 navigates the distal tip assembly 40 of the catheter 21 to a target location within the patient's body (the patient's heart 26 in this example) using, for example, a manipulator 32 near the proximal end of the catheter 21, or by utilizing other catheter navigation techniques known in the art or that will become more widely known in the future. Exemplary catheters and imaging assemblies that enable deflection and rotation are described in detail in U.S. Patent Nos. 9,980,786, 10,537,306, and U.S. Patent Application Publication No. 2020-006134, the disclosures of which are all incorporated herein by reference.

[0017] In the exemplary embodiment shown in detail in insets 25 and 45, imaging device 50 is configured to image the left atrium of heart 26. As shown in inset 45, imaging device 50 in this example is an ultrasound imaging device including a 2D array of multiple ultrasound transducers 53 (e.g., 32 x 64 ultrasound (US) transducers). Inset 45 shows imaging device 50 navigated to an ostium 54 of a pulmonary vein in the left atrium. Imaging device 50 can image a section of the inner wall of the ostium. Using position data provided by position sensor 52 and registration with imaging device 50, system 20 can determine the spatial coordinates of all pixels / voxels within the imaged section obtained by imaging device 50. An example of a suitable 2D array is described in D. Wildes et al., "4-D ICE: A 2-D Array Transducer With Integrated ASIC in a 10-Fr Catheter for Real-Time 3-D Intracardiac Echocardiography," in IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol. 63, no. 12, pp. 2159-2173, December 2016, doi:10.1109 / TUFFC.2016.2615602, which is incorporated herein by reference in its entirety.

[0018] It should be noted that the imaging device 50 is typically associated with or includes an imaging controller (such as 50A specifically illustrated in the figures) adapted to control / adjust image capture parameters of the imaging device, such as the field of view (FOV), depth of field (DOF), imaging device, dynamic range, gain, and / or sensitivity of the imaging device. Optionally, if the imaging device 50 has active illumination, the imaging controller may be adapted to adjust the gating time interval of image capture relative to the intensity and / or illumination timing of the active illumination. In various implementations, the imaging device may be operated in a snapshot mode in which the entire FOV of the imaging device is captured instantaneously and / or in a scanning mode in which the FOV of the imaging device is scanned / steered to generate the image. In such implementations, the imaging controller may also be adapted to control parameters of the snapshot mode and / or the scanning mode. Furthermore, the imaging device 50 is typically associated with or includes an image preprocessor (such as 50C specifically illustrated in FIG. 3A ) adapted to process / combine image portions captured from the imaging device and generate therefrom an nD representation of the image captured by the imaging device. For example, the image preprocessor may be adapted to combine multiple 2D images of different FOVs taken at substantially similar times to generate a volumetric (3D) image, and / or combine multiple such volumetric images to form a video (4D image). An ultrasound catheter within the scope of the present invention may be a 4D ultrasound catheter equipped with a two-dimensional (2D) ultrasound transducer array for generating three-dimensional (3D) or four-dimensional (4D) ultrasound images. In this context, the term "3D ultrasound image" refers to an ultrasound image representing a specific volume in three dimensions. The term "4D ultrasound catheter" refers to a catheter incorporating a 2D array of ultrasound transducers. The term "4D ultrasound image" refers to a time series of 3D ultrasound images of a specific volume acquired by a 2D array. A 4D image can be considered a 3D moving image, with the fourth dimension being time. Another way to describe a 4D image (or rendering) is as a time-dependent 3D image (or rendering).When used in the heart, a 4D ultrasound catheter is sometimes referred to as a "4D intracardiac echocardiography (ICE)" catheter. The catheter may also include an integrated location sensor, such as a magnetic position sensor, pre-aligned with the 2D array based on a known relative position and orientation on the catheter shaft between the location sensor and the 2D array. The 2D array generates a 3D sector-shaped ultrasound beam occupying a defined solid angle (such a beam is referred to herein as a "wedge," as opposed to the "fan" of a 1D array). Thus, the 2D array can image a 2D section of the interior wall of an organ, such as a heart chamber. Because of the integrated location sensor and its pre-alignment with the 2D array, the spatial coordinates of all voxels in the imaged section are known.

[0019] It should be understood that in some implementations, the imaging controller and / or image preprocessor may be located together with (e.g., as an integral part of) the imaging device 50, or in some embodiments, the imaging controller and / or image preprocessor may be remote from the image sensor (see 50B in FIG. 3A) and may be implemented, for example, as part of system 20 (e.g., as part of its computerized system 39) or in a separate system / driver.

[0020] The control console 24 of the system 20 includes a computerized system 39 having suitable front-end and interface circuitry 38 for receiving signals from the catheter 21 and, optionally, for applying therapy via the catheter 21, and, optionally, for controlling other components of the system 20.

[0021] The position sensor 52 is typically associated with the positioning system 34 of the system 20, which processes position signals obtained from the position sensor 52 to determine the position of the catheter distal tip assembly relative to the patient's body (i.e., indicative of the position of the imaging device 50 relative to the patient's body). In some embodiments, the position sensor 52 operates to sense signals indicative of its position and orientation (collectively referred to herein as "position") based on magnetic / electromagnetic fields generated by the magnetic / electromagnetic field generator 36. In such embodiments, the positioning system 34 includes the magnetic field generator 36 and drive circuitry (not specifically shown) configured to drive the magnetic field generator 36 to generate magnetic fields usable by the position sensor 52 to sense its position. Typically, the magnetic field generator 36 is positioned at a known location outside the patient 28, for example, beneath the table 29 on which the patient 28 lies. The magnetic fields generated thereby can therefore be used as a reference coordinate frame for tracking the position of the catheter 21 within the body of the patient 28. For example, during navigation of the catheter distal tip 40, the position sensor 52 senses the magnetic field provided by the magnetic field generator 36 and, in response, provides position data / signals to the system indicative of the position (location and orientation) of the distal tip 40 of the catheter 21. The position data / signals may be, for example, magnetic field signals sensed by the sensor and / or data / signals further processed from the sensed signals. The console 24 receives the position data / signals from the position sensor 52 and thereby determines the location and orientation of the imaging device 50 within the body of the patient 28. Position and orientation sensing methods using external magnetic fields have been implemented in a variety of medical applications, for example, in the CARTO™ system manufactured by Biosense Webster, and are described in detail in U.S. Pat. Nos. 6,618,612 and 6,332,089, WO 96 / 05768, and U.S. Patent Application Publication Nos. 2002 / 0065455, 2003 / 0120150, and 2004 / 0068178, the disclosures of which are all incorporated herein by reference.

[0022] It should be noted that system 20 is not limited to the particular magnetic / electromagnetic field-based positioning system described above, but may alternatively or additionally be implemented using other location techniques, such as by impedance-based position tracking or other techniques. Details of impedance-based position tracking techniques are described in U.S. Patent Nos. 7,536,218, 7,756,576, 7,848,787, 7,869,865, and 8,456,182.

[0023] As mentioned above, according to some embodiments of the present invention, the system 20 is adapted to generate isolated and / or cropped images of the target anatomical structure for presentation to an operator or physician 30 using the system.

[0024] In this regard, it should be noted that the term anatomy is used herein to refer to one or more portions of one or more body anatomy in a patient's body. It should also be understood that the terms isolated image and cropped image are both used herein to designate images capturing the anatomy of interest captured from the body of the patient 28, but with reduced presentation of other tissues / features not associated with / belonging to the anatomy of interest (e.g., reduced presentation of surrounding tissues / fluids, etc.) so as not to obscure the presentation of the anatomy of interest. Specifically, the term isolated image is used herein to designate an image captured by the imaging device 50 using imaging device acquisition parameters that are adjusted to reduce the capture of tissues / features / fluids not associated with the anatomy of interest. The term cropped image is used for a captured image (isolated or not) that has been further processed / cropped to remove / blank out any such features / tissues appearing therein that are not associated with the anatomy of interest.

[0025] To achieve this, system 20 (e.g., console 24) includes systems 100 and / or 300 according to embodiments of the present invention, which are adapted to generate isolated / cropped images of the anatomical structure of interest.

[0026] Systems 100 and / or 300, described in embodiments in more detail below, may be implemented as computerized systems and may include hardware and / or software configured and operable to generate separated / cropped images. In some embodiments, systems 100 and / or 300 may be implemented in computerized system 39 of system 20. Computerized system 39 may include, for example, a general-purpose computer or other computerized system that is programmed with software to perform the functions described herein. The software may be downloaded to the computer in electronic form, for example, over a network, or alternatively or additionally, may be provided and / or stored on non-transitory, tangible media, such as magnetic, optical, or electronic memory.

[0027] System 100 may, for example, be connectable to positioning system 34 (and catheter positioning sensor 52) and imaging device 50 of catheter 21, and may be adapted to utilize position data / signals obtained from position sensor / system 52 / 34 to operate imaging device 50 to capture isolated images of the target anatomical structure. System 300 may, for example, be adapted to acquire images (e.g., captured by imaging device 50) along with position data indicative of the location within the patient's body where the image was captured, and optionally along with acquisition parameters of imaging device 50 where the image was captured, and process the images based on the position data (optionally also using the acquisition parameters) to generate a cropped image of the target anatomical structure.

[0028] In this regard, in some embodiments of the present invention, system 100 and / or 300 facilitates the automatic generation of separate or cropped images of each anatomical structure captured by imager 50 based on the position of the imager when the image is taken. Indeed, once an image captured from a particular location within a patient's body is acquired by system 100 or 300 along with positional data indicative of that location, system 100 or 300 can operate to automatically determine which anatomical structures should be present in the image. This may be based on the positional data of the image, which may be used to assess the field of view (FOR) within the patient's body from which the image was taken, and optionally also on data indicative of capture parameters of the imager associated with the image, which may be used to more accurately assess the actual capture region (CR) within the patient's body that is captured in the image. Thus, systems 100 and / or 300 can facilitate data access to a knowledge base indicating the locations / positions / models of various anatomical structures within the patient's body and can be adapted to infer from the knowledge base which anatomical structures should be present in the image using FOR / CR ​​data inferred based on the position of the imaging device and optionally its acquisition parameters.

[0029] Referring to FIG. 2A, an example of an image M0 captured from the FOR of the imaging device 50 when positioned at a particular location within a patient's body is shown (this image is also referred to below as an initial image). In this non-limiting example, the initial image M0 is a volumetric / 3D image of the entire FOR of the imaging device taken from within the patient's heart in preparation for a transseptal procedure. In this initial image M0, the fossa ovalis is captured but is obscured by other tissues surrounding it (e.g., tissues in the near field and / or far field from the fossa ovalis relative to the imaging device). FIG. 2B shows an isolated image M0 of the fossa ovalis as obtained by operation of the system 100. R3 illustrates an example of a fossa ovalis image captured by a patient's ventricle (VV) 100. In this example, the fossa ovalis was automatically targeted as the anatomical structure of interest by system 100 based on the position data of imager 50. To this end, it should be noted that based on the position of imager 50, and optionally also based on its acquisition parameters, either of systems 100 / 300 can automatically "know" (e.g., utilizing a knowledge base) the position FOR of imager 50 within the patient's body (e.g., "know" that imager 50 "sees" from the right atrium to the left atrium, i.e., R to L, in this example), and can optionally also determine (e.g., utilizing the acquisition parameters of the imager) the anatomical structure that the imager will be focused on and captured.

[0030] Thus, system 100 can optionally automatically determine / assess the target anatomy (target) based on the imager position and optionally other capture parameters, and thereby optionally operate to automatically generate the cropped / separated imager. In the example of FIGS. 2A-2C, the imager was focused / adjusted to capture a target anatomy (target) relatively close to imager 50 (in this case, the fossa ovalis). Similarly, system 300 may also automatically determine the target anatomy from initial image M0, and may be adapted / operated to automatically crop the initial image M0 itself, or another image captured from imager 50, to the target anatomy (e.g., by removing voxels to the side of the target anatomy from initial image M0 and / or removing near-field and far-field voxels in front and behind the target anatomy relative to the imager position when image M0 was captured).

[0031] FIG. 2B shows the resulting isolated image M when system 100 is adapted / operated to (e.g., automatically) capture isolated images of the fossa ovalis. R, which in this case has been set by the system (e.g., manually) or otherwise automatically determined as the anatomical structure of interest (e.g., such automatic determination may be based on positional data and optionally acquisition parameters of the imaging device 50 when capturing the initial image M0 shown in FIG. 2A). For this purpose, the separated image M R To obtain the separated image M, the system 100 operates by adjusting the capture parameters of the imager 50, such as the field of view, depth of field, and sensor gain, to optimize capture of the target anatomy (the fossa ovalis) from the position where the imager is located, while reducing capture of its surroundings. The dashed white line in the image is provided herein to illustrate the FOR of the imager, as captured in its entirety in the initial image M shown in FIG. 2A. R , the structure of interest, the fossa ovalis, is captured by system 100 by adjusting the capture parameters of imaging device 50.

[0032] In some embodiments of the present invention, systems 100 and / or 300 facilitate user selection of a particular anatomical structure of interest for which an isolated or cropped image, respectively, is to be generated. To this end, optionally, systems 100 and / or 300 are associated with / connected to user interface devices (e.g., display 27 and user input controls of console 24) and adapted to receive data from an operator indicating the anatomical structure for which an image is to be isolated / cropped. For example, in embodiments, an unisolated / uncropped image, such as M0 shown in FIG. 2A , captured by imaging device 50 from the location where catheter 21 is positioned may be presented to the physician on display 27. Initial image M0 may be, for example, a 3D / volumetric image as shown in FIG. 2A (e.g., that the physician / operator may navigate or slice to identify structures of interest to the physician / operator), or may be a 2D image, such as a 2D slice of an image captured by imaging device 50 (e.g., an ultrasound image slice). The operator may then mark / select one or more points or regions on the initial non-separated image that represent at least one anatomical structure for which the operator wishes to create a separated image(s). In various implementations, the selection may be made, for example, by marking one or more points / boundaries (e.g., rough boundaries) on the presented image that designate the anatomical structure of interest, or by selection from a list of anatomical structures (e.g., a list of anatomical structures automatically determined as expected to be included in the image (e.g., or in the FOR of the imager)) based, for example, on a knowledge base and the position of the imager. System 100 / 300 determines the anatomical structures of interest to be separated and imaged from initial image M0 or cropped out of the initial image based on the selection / marking and the position of catheter 21 / imager 50 relative to the patient's body.

[0033] In this regard, FIG. 2C shows an image M cropped from the initial image M0 shown in FIG. 2A based on a user selection. c2B illustrates an example of an image capture system in which the initial image M0 is captured. Indeed, in this case, automatic identification of the anatomical structure of interest based on the position of the imaging device and the capture characteristics of the initial image M0 may have identified the fossa ovalis as the anatomical structure of interest (as shown with reference to FIG. 2B). However, in this case, the user / operator was actually particularly interested in more clearly viewing (in isolated / cropped form) the left pulmonary vein, which also appears in the initial image M0. Therefore, the operator in this case utilized the user interface to mark / select the specific anatomical structure of interest (the left pulmonary vein) that the operator wanted to view, and system 300 cropped the initial image M0 according to this selection. It should be noted that such cropping may also be performed on another image and / or may be performed, for example, by system 100, optionally on an already isolated image acquired / generated thereby. It should be understood that alternatively or additionally, in a similar manner, system 100 may also be adapted to obtain a user selection (e.g., from a user interface) and generate an isolated image of the selected anatomical structure thereby.

[0034] As described in more detail below, systems 100 and / or 300 utilize models, such as morphological models or machine learning models, to generate isolated / cropped images of the target anatomy. Based on automatically identified and / or user-selected target anatomy, systems 100 and / or 300 retrieve an appropriate model and utilize it for capturing isolated images and / or cropping the captured images.

[0035] A system 100 according to an embodiment of the present invention will now be described in more detail with reference to Figures 3A and 3B, which provide a block diagram and a flow chart illustrating the configuration and operation of system 100. System 100 is adapted to generate isolated images of anatomical structures. System 100 is connectable to a catheter 21 having an imaging device 50 and a position sensor 52 at its distal tip 40.

[0036] The imager 50 is capable of capturing a volumetric image of a desired FOV and a desired depth of field (DOF) within its field of view (FOR). For clarity and without being limited to the non-limiting example of FIG. 3A, the imager 50 is shown to include three functional components, including: (i) Image sensor 50B, which may include one or more image detectors / transducers (e.g., sound / ultrasound transducers in the case of ultrasound imaging devices, and / or light or other types of electromagnetic field detectors in the case of other types of imaging devices), optionally image scanning utility if a scanning scheme is employed by the imaging device, optionally active lighting utility if active lighting is used by the imaging device, and optionally imaging "optics" (appropriate for the type of field sensed by the imaging device, whether sound or electromagnetic (e.g., light)) or other beamforming utility for forming an image signal from the detector signals. (ii) an imaging controller 50A adapted to adjust one or more operating parameters of the imaging device that affect the extent of the region CR captured by the imaging device 50 during operation; (iii) an image preprocessor 50C that processes signals received from the image sensor 50B during image capture and constructs therefrom a volumetric image of the captured region CR. As will be appreciated by those skilled in the art of imaging, the image preprocessor may be adapted to perform various image processing operations, which may depend on the specific configuration of the imaging device 50 and the imaging modality used, including, for example, stitching image slices acquired during an image scan and other operations such as balancing signals acquired from different image detectors / pixels to obtain the following volumetric image result; determining voxel depth positions based on the time difference between a pulse of active illumination (if used in the imaging device) and the sensed signals; determining the lateral positions of voxels based on the simultaneous scans with which the sensed signals are associated; and / or beamforming the sensed signals to construct the volumetric image or its voxels. To this end, the imaging device 50 used in this embodiment of the present invention may be any type of imaging device that allows specific control of the position and range / span of the region CR within the field of view of the imaging device to be captured by the imaging device.

[0037] In this example, without loss of generality, an ultrasound imaging device is specifically exemplified.

[0038] The position sensor 52 can provide position data indicating the position of the ultrasound imaging device 50 within the body of the patient 28. In the following, the imaging device 50 combined with the positioning system 34 will also be referred to as a tracking imaging system (101 in FIG. 3A and / or 301 in FIG. 4B), which is adapted to provide / capture / store images processed by the system together with their respective position data and, optionally, data of the acquisition parameters with which the images were acquired, indicating the region CR within the body that is captured by each image.

[0039] Based on the position data, system 100 is configured and operable to operate imaging device 50 to capture one or more 2D and / or 3D images of at least a portion of the body anatomy (anatomical structure), such that the 2D and / or 3D separated images present at least a portion of the body anatomy substantially separated from other unassociated body tissues (e.g., nearby tissues). To achieve this, system 100 is adapted to adjust one or more capture parameters of the imaging device, such as its FOV and / or DOF, or other imaging parameters, such that the region CR being captured by the imaging device closely matches a region of interest ROI within the patient's body occupied by the portion of the body anatomy desired to be captured.

[0040] In this regard, it should be noted that the phrase “field of regard (FOR)” is used herein to designate a volumetric region in front of the position of the imaging device 50 that can be captured / perceived when the imaging device 50 is positioned therein. It should also be noted that the terms field of view (FOV) and depth of field (DOF) are used herein to designate capture parameters and refer to the actual capture region CR within the FOR that is captured by the sensor / transducer of the imaging device 50. More specifically, the term FOV relates to the lateral / angular extent of the region captured by the imaging device 50 (e.g., lateral to the general direction / axis along which the imaging device 50 is oriented to capture, which may be fixed or steerable relative to the sensor of the imaging device 50, e.g., depending on the configuration of the imaging device 50). The term DOF is used herein to designate the span between the nearest and farthest points within the captured region CR that appear acceptably in focus / “sharp and not blurry” in the captured image. In this regard, for some types of imaging device 50 usable by system 100 (e.g., imaging device operation through a scan of a region of interest), the DOF can be set individually for each pixel or group of pixels (e.g., rows) in an image to be captured, as shown, for example, in FIG. 3C . In some embodiments, particularly when imaging device 50 incorporates active illumination for echo detection and respective time gating capabilities, system 100 may be adapted to eliminate or reduce capture of regions before or after a desired DOF, e.g., by appropriate time gating. Similarly, for some types of imaging device 50, a cross-section of the FOV captured by the imaging device may be set by system 100 to have a non-regular / non-pre-fixed shape. Accordingly, in various embodiments, system 100 may be adapted to adjust FOV and / or DOF capture parameters to adapt the capture region CR to the subject's anatomy (e.g., in some cases, the shape of the capture region CR may be morphologically adapted).This facilitates adjustment of such parameters so that the shape of the capture region / volume CR substantially conforms to the anatomical structure of interest within the patient's body located therein, while areas outside the specified capture region / volume CR in which the anatomical structure of interest is located are excluded from capture or are captured at reduced intensity within the image.

[0041] It should be noted that the terms illumination and active illumination are used herein to designate any type of illumination used by an imaging device during acquisition, and may relate, for example, to ultrasound illumination in the particular case of ultrasound imaging device 50, and / or other types of active illumination (e.g., optical light or any other type of electromagnetic field / radiation, such as may be used by various types of imaging devices to illuminate the acquisition area). Terms such as gating, gated, and time-gating are used herein to designate an operating mode of an imaging device in which a sensor or pixel (e.g., a sub-sensor / detector / transducer) is operated in synchronization with the timing of the active illumination so as to sense echoes / reflections of the active illumination arriving only from a particular DOF for that sensor (and for that pixel).

[0042] Furthermore, in types of imaging devices that use beam steering and / or beam forming of either active illumination or echoes / reflections received / sensed by the image sensor, it should be noted that the beam steering / beam forming scheme can be adjusted and controlled by system 100 to control the actual shape of the region CR being captured. For example, when beam forming is used for active illumination, the active illumination may be beam formed to illuminate / focus only specific portions within the FOR, so that capture includes only those illuminated portions. Similarly, alternatively or additionally, when beam forming is applied to returning echoes / reflections, the focus of the beam formed echoes / reflections may be set to echoes arriving only from specific portions within the FOR (e.g., so that those echoes constructively interfere), while echoes / reflections from other portions of the FOR are attenuated (e.g., via destructive interference) so that capture includes only those portions that are at the focus of the echo beam forming. Similarly, beam steering can also be used to control the cross-sectional shape of the FOV.

[0043] Additionally, other acquisition parameters of the imaging device, such as the sensor / transducer gain and / or its operating dynamic range, and / or illumination intensity / frequency (if active illumination is used), may be set / optimized using FOR to generate / sense echoes / reflections arriving from certain selected regions or body tissue types, while generating / sensing echoes / reflections from other regions / tissue types at lower intensities.

[0044] To this end, embodiments of the present invention take advantage of the fact that adjustable capture parameters in various imaging techniques allow the size and / or shape and / or location of the capture region CR to be adjusted to relatively closely fit the shape of the target anatomy, while keeping most of the FOR area outside the "fitted" capture region CR excluded from (reduced in) the captured image, as described, for example, with reference to Figures 3A-3B. Thus, by identifying the target anatomy, or a portion thereof, desired to be imaged, and determining the area that the target anatomy occupies within the FOR of the imaging device, the imaging parameters (one or more of them) can be adjusted so that the capture region CR of the imaging device fits the target anatomy, thereby facilitating isolated capture of the anatomy.

[0045] To achieve this, the system 100 includes one or more processing utilities 110 configured and operable to generate one or more 2D and / or 3D separated images of at least a portion of the subject's body anatomy. The one or more processing utilities 110 of the system 100 may be implemented by software and / or hardware and may, for example, conceptually include the following functional processing utilities (which may actually be implemented by one or more processors): - a field of view (FOR) processing utility 112 connected directly or indirectly (e.g., via the positioning system 34) to the position sensor 52 of the catheter 21 and adapted to process position data received from the positioning system 34 / position sensor 52 to determine the volumetric ocular field of view FOR range of the imaging device relative to the reference coordinate frame of the positioning system 34. Since the patient's body is generally aligned with the positioning system 34 (e.g., by placing the position pad / position field generator 36 of the positioning system 34 at a predetermined position relative to the patient's body), the volumetric ocular field of view FOR is actually determined relative to the patient's body. The model provider utility 113 is adapted to provide a model representing at least a portion of a subject's body anatomy desired to be captured. The model provider may be adapted to provide one or more models of anatomy expected to be present within the volume FOR of the imaging device 50 within the patient's body, and / or a model of a specifically selected anatomy (or portion thereof) selected by the physician / operator via the user interface 115 described below. - An optional User Interface (UI) 115 (e.g., including a display and input controls) adapted to allow a user to select a region of interest within the FOR of the imaging device in which an anatomical structure or part thereof for which isolated imaging is desired resides. - A model processing utility 114 adapted to receive a model of the target anatomical structure from a model provider and input from an imaging device indicating image content captured from the FOR, utilize the model to image the content, and identify a region of interest ROI within the FOR in which the target anatomical structure is present. The acquisition controller 116 is adapted to acquire data indicative of the ROI (its location and extent within the FOR) and adjust one or more acquisition parameters of the imaging device 50 to optimize the acquisition of at least a portion of the body anatomical structure by the imaging device 50 and reduce the acquisition of visual information captured from the background / tissue surrounding at least a portion of the subject's body anatomical structure. The acquisition controller 116 adjusts the acquisition parameters such that the captured region CR more closely matches the region of interest ROI in which the subject's body anatomical structure is present within the FOR. This is achieved based on processing performed by the model processor 114 to determine the position / location of the subject's body anatomical structure within the imaging device's FOR based on the model AM. The acquisition controller 116 is connected to the imaging device 50 (e.g., to the imaging controller 50A therefor) to appropriately adjust the imaging parameters to acquire the ROI using the imaging parameters. The acquisition utility 116 is adapted to operate in response to the imaging device 50 capturing an ROI using the capture parameters, and acquires from the imaging device 50 (e.g., its imaging pre-processor 50C) a separated volumetric image of the target anatomical structure within the ROI captured using the adjusted parameters. - The optional rendering utility 118 is adapted to obtain at least one separated volumetric image of the anatomical structure of the target ROI to generate one or more 2D and / or 3D separated images of said at least a portion of the target's body anatomical structure, wherein at least a portion of the target's body anatomical structure appears substantially separated from body tissue not associated therewith.

[0046] The operation of the system 100 will now be described in more detail with reference to Figure 3B, which is a flowchart of a method 200 for generating separated images of an anatomical structure of a subject, according to an embodiment of the present invention.

[0047] In operation 210, based on position data obtained from the position sensor 52 (e.g., from its associated positioning system 34), the volumetric ocular field of view (FOR) of the imaging device 50 relative to (e.g., within) the body of the patient 28 is determined (e.g., by the FOR processor 112 described above). Indeed, the positioning system (in communication with the position sensor 52 on the catheter 21) receives signals / data from the position sensor 52 indicative of the location and orientation of the distal end 40 of the catheter 21 at which the imaging device 52 resides. The positioning system 34 operates in registration with the patient's body, thereby determining the location and orientation of the imaging device 50 relative to / within the patient's body. This position and orientation data of the imaging device 50, along with predetermined data indicative of the imaging device's viewing capabilities (e.g., its maximum FOV angle and maximum DOF range), are processed to determine the FOR of the imaging device 50 within the patient's body.

[0048] In operation 220, a model of at least a portion of the body anatomical structures present in the FOR is retrieved / obtained, for example, by model provider 113 of system 100. In some embodiments, the model may be automatically retrieved based on data indicative of the FOR of imaging device 50 acquired in 210 relative to the patient's body, optionally also based on acquisition parameters with which the imaging device is configured / set (which allow a physician to evaluate the anatomical structures of interest), and further based on knowledge base data (e.g., indicating the location of various anatomical structures within the body) from which information indicative of the anatomical structures included in the FOR may be determined / evaluated (e.g., according to the alignment between the FOR and the patient's body).

[0049] Alternatively or additionally, in some embodiments, operation 220 may include capturing at least one image of the FOR or a portion thereof from the imaging device (see M0—initial image in FIG. 3A ) and presenting it to the physician / operator of system 100 and / or method (200) to more accurately identify at least a portion of the target body anatomy. The initial image M0 may be presented, for example, via user interface 115 or its display, and in response to the presentation, the system may obtain input data (selection / marking) from the physician / operator indicating a selected region of interest (ROI) or particular anatomical structure within the FOR of the imaging device for which the physician / operator desires to obtain an isolated image. In some implementations, the initial image M0 may be, for example, a 2D slice of at least a portion of the FOR of the imaging device, or a volumetric image thereof, which the physician / operator can manipulate via UI 115 to display the desired portion.

[0050] Thus, based on the anatomical structure identified in the FOR of the imaging device and / or based on user selection / marking of the target anatomical structure therein, and further based on the position / FOR of the imaging device (determined from the position data of the position sensor), the target anatomical structure is identified and the model provider 113 retrieves a corresponding model AM of the target anatomical structure (e.g., from a data repository of anatomical structure models).

[0051] To this end, in some embodiments, the model AM includes or consists of a morphological model of the target's anatomy (e.g., a so-called point cloud model or other type of morphological model), e.g., indicating at least one of its shape, size, and optionally, its typical location within the body. Generally, such a morphological model AM may be a generic morphological model of the target's anatomy, or in some cases, a patient-specific morphological model. To this end, in the case of a generic model AM, it may include data indicating at least one of the characteristic shapes, characteristic sizes, and / or characteristic locations of at least some of the target's body anatomy / anatomical structure. Alternatively or additionally, such a morphological model AM may be a patient-specific model indicating the shape and / or size and / or location of at least some of the target's body anatomy / anatomical structure for a particular patient 28. Still alternatively or additionally, such a morphological model AM may be a condition-specific model indicating the shape and / or size and / or location of at least some of the target's body anatomy / anatomical structure when the patient 28 has a particular condition / pathology from which the patient 28 suffers.

[0052] In the latter case, such a model may have been previously acquired / prepared, for example, from previous images of the patient (e.g., from CT images or other types of medical images of the patient), or may have been previously prepared (e.g., by physician 30) by performing a mapping procedure that maps the target anatomical structure within the patient's body. In such a mapping procedure, the physician may, for example, utilize a "mapping" catheter (which may be catheter 21 or another catheter equipped with a position sensor such as 52) to map multiple locations on the target anatomical structure within the patient's body (whereby, during such mapping, the position of the distal end of the catheter, and possibly other sensed properties such as tissue or ECG properties, are recorded in the model at the point where the distal end of the "mapping" catheter is over the target anatomical structure).

[0053] To this end, in some embodiments, the system 100 includes at least one mapping medical device 41 (e.g., a mapping catheter) configured and operable to map an anatomical structure within a patient's body. The mapping medical device 41 includes a position sensor (not specifically shown) thereon and is adapted to receive user input for mapping at least a portion of the body anatomy. For example, upon receiving a user input indicating that a location where the catheter is present belongs to the target body anatomy (to be mapped), a signal indicative thereof is provided to the system 100. The system 100 (e.g., its one or more processors, such as the model provider 113, and / or the positioning system 34) is adapted to track the position of the mapping medical device and record the tracked positions indicated as belonging to the body anatomy being mapped, thereby constructing a patient-specific model of at least a portion of the target body anatomy. In some implementations, the system 100, e.g., its model provider 113, is adapted to record these tracked positions associated with at least a portion of the target body anatomy (e.g., in the form of a point cloud) to form a model indicative of the shape of that portion of the patient's body anatomy. Further, optionally, in some implementations, the mapping medical device 41 may include one or more sensors adapted to sense one or more tissue properties of at least a portion of the patient's body anatomy at these tracking locations, and the system 100 may include data indicative thereof in the model. More specifically, the tissue property data may include information indicative of the appearance of one or more tissues in various portions of the body anatomy and / or surrounding areas thereof when imaged by the imaging device 50.

[0054] Thus, in some embodiments, the morphological model AM may also include tissue data indicative of specific properties of one or more tissue types of the target anatomical structure. For example, such tissue data may include spectral information indicative of tissue spectral response (absorption / reflection / scattering) of different spectral regimes of the field / radiation being imaged by the imaging device 50. The tissue data may include general data indicative of the general anatomical structure of the type recorded in the model and / or tissue properties of this type of anatomical structure with a particular condition / pathology suffered by the patient, and / or patient-specific tissue data acquired by a user of the mapping medical device / catheter 41, for example as described above.

[0055] Alternatively or additionally, in various embodiments, the model AM retrieved by the model provider 113 may include a machine learning (ML) model trained to process an input data image (e.g., an initial image M0 captured from the FOR) and output data indicative of a ROI region (e.g., a region occupied by the anatomical structure of interest) within the FOR (e.g., its size, shape, and / or location) in which the anatomical structure of interest resides. The machine learning (ML) model may be used in addition to or instead of the morphological model described above. As will be appreciated by those familiar with the art of machine learning, this type of ML model may include parameters (e.g., weights) of one or more neural networks pre-trained to recognize and / or classify anatomical structures of the type of anatomical structure of interest within an image captured from the FOR (e.g., the initial image M0) and determine the ROI therein occupied by the anatomical structure of interest. Additionally, as will be understood by those skilled in the art after learning of the present invention, training of the ML model may be performed in advance for each anatomical structure of the target, for example, by utilizing training data including multiple images in which the anatomical structure of the target appears and adjusting the weights of the ML model (e.g., via gradient descent) until the model is trained to properly classify / recognize ROIs in the images in which the anatomical structure of the target is present. Training may be supervised or semi-supervised / unsupervised (in the latter case, a morphological model, a general model, or a patient-specific model corresponding to the input images may be used to modify and train the model in an unsupervised or semi-supervised manner).

[0056] Thus, in operation 220, the system 100 retrieves the model AM based on which a region of interest ROI in which the anatomical structure of interest resides / occupies can be identified in the image acquired from the imaging device 50.

[0057] In operation 230 (which may be performed, for example, by model processor 114), an anatomical model AM is used to determine / assess a region of interest ROI within FOR that is occupied by the anatomical structure of interest. The region of interest may be determined, for example, in terms of its size, shape, location, and / or the "voxels" it occupies within FOR. The model AM may be, for example, a morphological model or a machine learning (ML) model as described above, and in some implementations may be a general or personalized model of the anatomical structure.

[0058] In some implementations (e.g., when the model is a morphological model), the system 100 or its model processor 114 determines / evaluates the region of interest ROI by aligning and / or matching (e.g., so-called "best fit") the model with one or more initial images (e.g., initial image M0) captured from the FOR. In some embodiments, for example, when the model is a generic model or when the shape of the target's anatomical structure changes (e.g., due to its movement), achieving the best fit between the models can include, for example, morphing / warping the shape of the model to generate its morphed shape, so that the morphed shape is adapted to the captured initial image (e.g., most of the pixels / voxels representing the target's anatomical structure in the captured image are "covered" by the morphed model without covering pixels / voxels not representing the target's anatomical structure, or without covering such pixels / voxels as much as possible by the model). In this regard, as will be understood by those skilled in the art after learning of the present invention, morphing / warping of the morphological model can be applied until a best fit is achieved or until a certain morphing threshold is reached. The morphing / best fit can be based on a partial image of the FOR, which may include only one or more 2D slices or portions of the volumetric image. In embodiments where the morphological model includes data indicative of tissue properties of the target anatomy, these properties, which may include, for example, the spectral response / characteristics of the tissue, can be used in the fitting / registration to determine the best fit (as long as they are evident in the initial image M0 to which the model is fitted).

[0059] To this end, according to some embodiments, based on such matching, the system 100 or its model processor 114 maps between one or more regions (voxels) of at least one body anatomical structure present in the model AM and corresponding voxels (volumetric regions) in the FOR of the imaging device 50, thereby identifying the ROI occupied by the anatomical structure of interest in the FOR. Such mapping may be performed, for example, as follows: - the positional matching between different regions (voxels) of the body anatomy in the model and the corresponding pixels / voxels in the FOR part presented in the initial image M0, and - This may be based on one or more combinations of: - matching the tissue characteristics (and their spectral characteristics) indicated for different regions of the body anatomy in the model AM with the spectral data of the corresponding voxels / pixels in the initial image M0.

[0060] For example, in some embodiments, the mapping is determined based on a match of tissue properties while minimizing the model morphing required to achieve such a match to locations in the initial image.

[0061] Alternatively or additionally, as described above, in some embodiments, model AM may be or include an ML model trained to recognize / classify anatomical structures of interest in an image of a patient's body (e.g., initial image M0) and determine / estimate ROIs occupied by the anatomical structures in the image. In such embodiments, operation 230 may include running the ML model on the captured initial image M0, thereby generating data indicative of the ROIs (shape / size / location) within the FOR apparent in the initial image M0.

[0062] As will be appreciated, once the ROI is identified in the initial image M0, the location of the ROI relative to body coordinates can also be determined (considering that the initial image is captured along with position data of the imaging device 50 relative to the patient's body, as obtained by the position sensor 52).

[0063] Thus, in operation 240, which may be performed by the acquisition utility 116 after the ROI is determined, the system 100 utilizes the determined characteristics of the ROI (its shape, location, and / or size relative to body coordinates) and, optionally, the current position of the imaging device 50 (obtained from the position sensor 52) to set up / adjust / optimize appropriate acquisition parameters for the imaging device 50 to capture a substantially isolated image of the ROI by the imaging device 50. In other words, the acquisition parameters are adjusted such that the region CR being captured by the imaging device is reduced / adjusted to cover the ROI substantially exclusively (i.e., with as minimal a margin as allowed by the adjustment of the acquisition parameters), and operating the imaging device 50 with the adjusted acquisition parameters results in the acquisition of a substantially isolated image of the target anatomical structure. In particular, adjusting the capture parameters may include, for example, adjusting parameters affecting the FOV angle of the image capture device 50 so that the captured FOV substantially matches the angular range of the ROI relative to the image capture device 50, and / or adjusting the DOF of the image capture device (e.g., the range of distances from the image capture device 50 that are captured with acceptable resolution) to fit / match as closely as possible to the depth range of the ROI.

[0064] Depending on the type / technology of the imaging device, the acquisition parameters that are adjusted may include one or more of the acquisition parameters described below.

[0065] Adjusting parameters that affect the FOV of the imager may include, for example, any one or more of the following: - Adjusting the scanning angle of the imaging device (applicable when the imaging device operates in scanning mode), and / or For example, adjusting the zoom characteristics of the "optics" of the imaging device, where the imaging device comprises an optical system and the optical system facilitates zooming. In this regard, it should be understood that the term optics is used to denote any type of element that can manipulate fields / waves of the type sensed / imaged by the imaging device 50 (e.g., it does not necessarily relate to elements that manipulate optical fields, but also to elements of other types of fields that are imaged by the imaging device, such as acoustic lenses or metamaterial structures that can manipulate (refract / diffract) acoustic, ultrasonic or electromagnetic fields, alternatively or additionally). - Adjusting the angle of active illumination (applicable if the imaging device employs such illumination).

[0066] To this end, in some embodiments, parameters affecting the FOV of the imager are adjusted so that the FOV of the imager is reduced substantially closer to the ROI in which the anatomical structure of interest resides, in order to suppress capture of voxels located to the sides of the ROI, and thus the lateral extent of the region CR being captured by the imager is more closely matched to the lateral extent of the ROI.

[0067] Alternatively or additionally, adjusting parameters affecting the DOF of the imaging device may include, for example, any one or more of the following: In imaging devices with active illumination, such as ultrasound imaging devices, the gating time interval between the timing of the active illumination (e.g., pulse) and the timing of the operation of the sensor to capture the return signal (echo / reflection) is adjusted to thereby adjust the effective range of distance over which the sensor will accept / sense the return echo / reflection, thereby limiting the DOF to this range. In imaging devices with active illumination, the frequency(ies) of the active illumination are adjusted to affect / control the penetration depth of the active illumination, thereby adjusting the DOF captured by the imaging device. Indeed, as will be understood by those skilled in the art of ultrasound imaging, for example, utilizing active illumination with a lower ultrasound frequency generates a greater penetration depth of the illumination (e.g., sound), thereby facilitating more remote anatomical structures and / or a greater DOF. Conversely, at higher frequencies, closer structures are captured with higher resolution, while more distant structures are diminished from the image (because the active illumination does not reach them with sufficient intensity). In some embodiments, the sensor's response to the frequency of the returning echo / reflection (e.g., or filtering of such frequencies) may alternatively or additionally be adjusted to achieve some similar effect. - Adjusting the gain and / or active illumination intensity of the imaging device depending on at least one of the location / distance from the ROI to the imaging device and / or the type of tissue included in the target anatomy (e.g., as indicated by the model AM). As will be understood by those skilled in the art of imaging, such manipulation of sensor gain and / or active illumination intensity can affect the dynamic range of the sensor, thereby directly or indirectly affecting the range of distances over which image details are captured by the sensor. In imaging devices such as scanning imaging devices where beamforming techniques are used, the focus of the beamformed active illumination or beamformed return echoes / reflections may be adjusted to whittle the distance range of the desired DOF, thereby suppressing the detection of returns / echoes from distances outside that range. In imaging devices such as stare / snapshot imagers with adjustable apertures, the size of the aperture opening can be adjusted to produce images with a wider or narrower depth of focus (i.e., using a smaller or larger aperture, respectively), thereby adjusting the range of distances at which imaged details appear sharp in the image and blurring (thereby suppressing) imaged details outside that range.

[0068] Thus, in some embodiments, parameters affecting the depth of field DOF of the imager are adjusted such that the DOF of the imager is depth-constricted to fit substantially closer to the ROI in which the anatomical structure of interest resides, thereby suppressing capture of voxels located in front of or behind the ROI. To this end, by adjusting the FOV and / or DOF in the manner described above, the capture region CR of the imager 50 is adjusted to fit / match the ROI with no margin or only a small margin.

[0069] In this regard, and with reference to FIG. 3C , it should be noted that in some implementations, the margin between the capture region CR and the ROI can be further minimized by individually adjusting the DOF parameters for each subset of FOV angles being captured (e.g., such that at each subset of FOV angles the DOF is individually adapted to the actual depth range of the ROI). Indeed, in an imaging device operating in scanning mode, for example, the system 100 can apply different adjustments of the DOF parameters to different scanning angles. FIG. 3C illustrates this case, showing in a trivial manner a catheter 21 similar to that shown in FIG. 3A , with the capture region CR of the imaging device 50 adapted / retracted in this manner. As shown, in this example, the DOF captured by the imaging device is such that different sections of the FOV have different DOFs (e.g., DOF1, DOF2, DOF3, DOF4, DOF5, DOF6, DOF7, DOF8, DOF9, DOF10, DOF11, DOF12, DOF13, DOF14, DOF15, DOF16, DOF17, DOF18, DOF19, DOF20, DOF21, DOF22, DOF23, DOF24, DOF25, DOF26, DOF27, DOF28, DOF29, DOF20, DOF21, DOF20, DOF21, DOF22, DOF23, DOF24, DOF25, DOF26, DOF27, DOF28, DOF29, DOF30, DOF31, DOF32, DOF33, DOF34, DOF35, DOF36, DOF37, DOF38, DOF39, DOF40, DOF41, DOF42, DOF43, DOF44, DOF45, DOF46, DOF47, DOF48, DOF49, DO k , and DOF n The shape of the capture region CR is adjusted / changed over the scan angle of the imager along the FOV so that the image is imaged at a depth of field (as indicated by a dotted line). Thus, the shape of the capture region CR is adapted more closely to the shape of the ROI in which the anatomical structure of interest resides, optionally with a reduced margin, compared to when the DOF parameters are adjusted globally for the entire FOV.

[0070] It should be noted that in some embodiments, additional capture parameters may be adjusted to generate higher quality separated images of the ROI. For example, in some embodiments where the shape of the target anatomy is variable, e.g., when capturing a beating heart or portion thereof, system 100 may also be adapted to adjust the frame rate of the imaging (e.g., scan rate / shutter speed), whereby imaging with a fast shutter / high scan rate allows imaging of anatomy that is moving during imaging, and a lower frame rate can facilitate images with an improved signal-to-noise ratio (SNR).

[0071] Further, in operation 240, after setting the appropriate capture parameters, the system 100 (e.g., its acquisition utility 116) operates the imager 50 to capture an image M of the ROI by using the above capture parameters. R thereby capturing a volumetrically separated image M of the target anatomy. R Get.

[0072] In optional operation 250, the volumetric separated image is then further processed / rendered (e.g., by rendering utility 118 of system 100) to generate volumetric separated images M from different angles / perspectives and / or different 2D slices thereof. R This can facilitate presentation of the anatomical structures present within the anatomical structure and display thereof to the operator / physician 30 (e.g., via the UI 115).

[0073] In some cases, as mentioned above, the volume separated image M R presents a region of interest occupied by anatomical structures with some remaining margins that cannot be completely suppressed / eliminated by adjusting acquisition parameters. Therefore, in some embodiments of the present invention, the system 100 (e.g., its rendering utility 118) generates a separated image M Ris further processed to substantially remove any remaining margins that may appear around the anatomical structure, resulting in a cropped image M of the margin-free anatomical structure. C To achieve this, according to some embodiments of the present invention, the one or more processors 110 of the system may be adapted to generate a volumetric image M obtained from the imaging device 50 (or a 2D / 3D image rendered therefrom) by using a model AM of the subject's anatomical structure. R to identify voxels in these images that are not associated with the anatomical structure of interest and remove / blank said voxels. For example, if the model AM is a morphological model as described above, such processing may be configured to identify one or more regions (voxels) of at least a portion of the body anatomical structure present in the model AM and at least one volumetric image M R and using the map to generate an image M in which only voxels mapped to the model AM remain unblanked. C and cropping the image. If model AM is a trained ML model, such cropping procedures may be applied to provide the image as input to the model for receiving therefrom as output data indicative of voxels associated with the anatomical structure (e.g., in a manner similar to the model processing described in connection with operation 230 above). Operations of system 100 and / or its rendering utility 118 that may be incorporated in this embodiment of the present invention to render cropped images of the anatomical structure of interest are described in more detail below with reference to the embodiment of FIGS. 4A and 4B.

[0074] In some embodiments, the system 100 is adapted to generate a video of a portion of a subject's body anatomy separated / cut out from the tissue or other fluids surrounding it.

[0075] To achieve that, in such an embodiment, the system 100 generates a plurality of successive isolated / cropped images M of the portion of the subject's body anatomy for a plurality of respective successive time frames. R / M C and generating a plurality of successive separated / cropped images M from at least one desired angle of view or from a plurality of angles of view that vary continuously along the span of the time frame. R / M C The function is adapted to operate one or more processors 110 as described above to render a video of the subject's body anatomy with irrelevant tissue removed.

[0076] In this regard, it is noted that, according to some embodiments, system 100 is configured and operable to adjust imager acquisition parameters and capture images / videos of the ROI in real time and gram, thus enabling real-time capture of decoupled images / videos of the target anatomy. For example, these two operations of imager parameter adjustment (according to the catheter's position relative to the ROI) and corresponding image capture may be performed in real time (as an ongoing real-time loop) such that images are acquired and optimized for real-time rendering of the target anatomy in a decoupled manner (i.e., with its perimeter reduced in the captured / rendered image / video).

[0077] As mentioned above, embodiments of the present invention can be implemented using a catheter, such as catheter 21, in which various types of imaging device 50 can be placed. For example, imaging device 50 can be an ultrasound imaging device and / or an imaging device capable of imaging electromagnetic radiation / fields in the optical regime and / or other electromagnetic regimes. It should be noted, nevertheless, that the present invention is particularly advantageous for use with imaging devices, such as ultrasound imaging devices, that can be operated in situ and in vivo within a patient's body to image its internal organs. Additionally, imaging devices that utilize active illumination (such as most ultrasound imaging devices) and / or scanning techniques (as opposed to imaging devices that operate in snapshot mode) can advantageously provide enhanced control over the characteristics of the region captured thereby (e.g., in terms of DOF and / or FOV), thereby facilitating the capture of high-quality, separated images of the target anatomical structure by appropriate adjustment of their active illumination scheme / gating and / or their operation during the scanning of different scan sections.

[0078] 4A and 4B, which schematically illustrate a system 300 and method 400 for generating an image of an anatomical structure according to another embodiment of the present invention. The system 300 is adapted to process an image M (e.g., a volumetric or 3D image, or a video sequence thereof) acquired from within a patient's body and in which an anatomical structure of interest or a portion thereof appears, together with position data PD, to identify / recognize a region of interest (ROI) within the image M in which the anatomical structure of interest appears, and to crop the image M to the ROI to form a cropped image Mc (e.g., a 2D, 3D, or volumetric cropped image, or a cropped video sequence thereof) in which the anatomical structure of interest is separated / removed from other surrounding tissue.

[0079] The system 300 can be directly or indirectly connected to receive image data M and corresponding position data PD of images captured by a catheter 21 similar to that shown and described above. To this end, the system 300 may be connected to a tracking imaging system 301 and / or a data repository 303 to receive such image data M and corresponding position data PD therefrom.

[0080] For example, the tracking imaging system 301 may be similar to those described above and may be connectable to a catheter 21 having a distal tip 40 including an imaging device 50 capable of capturing volumetric images within the body of the patient 28 and a position sensor 52 capable of providing position data indicative of the position of the imaging device 50. The tracking imaging system 301 may include, for example, an image utility 302 adapted to obtain images M captured by the imaging device 50 of the catheter 21, and a positioning system 34 capable of processing position signals from the position sensor 52 of the catheter 21 and, optionally, receiving acquisition parameters under which the imaging device 50 was operated to capture the images M, to determine position data PD indicative of the position of the imaging device 50 relative to the patient's body at which each image M was captured (e.g., the position data PD may include data indicative of the imaging device FOR, which may be based primarily on the position of the imaging device, and / or data indicative of the region CR being captured by the image M, which may also be based on the acquisition parameters under which the images were acquired).

[0081] In some embodiments, the tracking imaging system 301 may be directly connected to the system 300 to provide the images M and corresponding position data PD thereto. Alternatively or additionally, in some embodiments, the tracking imaging system 301 is connectable to a data repository 303 (e.g., a data store or database) and adapted to store the images M and corresponding position data PD therein to enable their further processing by the system 300.

[0082] The system 300 then receives / obtains the image M and the corresponding position data PD either directly from the system 301 or indirectly from the repository 303, and processes / renders the image M based on the position data PD to generate a cropped image M of the target anatomy / body anatomy appearing therein. c The system 300 includes one or more processors 310 adapted to: - obtaining a model AM of the target anatomical structure appearing in the image M (e.g., by the model processor 314) and processing the image using the model AM to determine a region of interest (ROI - in the context of Figures 4A and 4B, used to designate a subset of image voxels / pixels) occupied by the target anatomical structure and around which the image should be cropped; and Rendering an image M (e.g., by a rendering utility 318) based on the identified ROI and cropping the image to fit the ROI, thereby generating a cropped image M of the target anatomy / body anatomy. c Generate.

[0083] To this end, system 300 typically includes or is associated with a model provider 313 (e.g., a repository of anatomical models) that can provide models of various body anatomical structures that may be of interest for cropping images to them. The model provider may, for example, be similar to model provider 113 described above with reference to FIGS. 3A and 3B and, as described above, may be adapted to provide morphological models and / or machine learning models of various body anatomical structures, which may be generic or patient-specific. To this end, for the sake of brevity, descriptions of these types of anatomical models AM, their content / use and / or operation will not be repeated in detail here, except to clarify that their configuration / content may be similar to the models described in detail above.

[0084] In some embodiments, system 300 is also optionally associated with a user interface utility 315, similar to interface utility 115 described above, that enables a physician and / or operator of system 300 to view the contents of image M, select / mark anatomical structures of interest (and portions thereof) appearing therein, and instruct system 300 to crop image M to the selected anatomical structures (and selected portions thereof). For brevity, a detailed description of user interface utility 315 will not be repeated here, although it will be understood that the description of interface utility 115 above also applies to user interface utility 315 in this embodiment.

[0085] The configuration and operation of system 300 will be further described below in detail in a mode with reference to a method 400 implemented by system 300, shown in FIG. 4B.

[0086] In operation 410, at least one initial image M and its respective position data PD are acquired by system 300, and target anatomical structures or portions thereof appearing in image M are identified. In some embodiments, the identification of target anatomical structures is performed automatically based on image position data PD indicating where image M will be captured within the patient's body and, optionally, other image capture parameters, and predetermined knowledge base data indicating anatomical structures expected / known to appear at such locations. Alternatively or additionally, in some embodiments, to more accurately identify portions of the target body anatomy, operation 410 may include presenting the captured image M to physician / operator 30, e.g., via user interface 315, in a manner similar to that described above, and, in response to the presentation, obtaining input data selections / markings from the physician / operator indicating selected regions of interest ROI or particular anatomical structures appearing in image M.

[0087] Based on the identified target anatomical structure / body anatomy, which may be done automatically or via user selection, in operation 420 a model AM of at least a portion of the target's body anatomy is retrieved, for example, by model provider 313 of system 300.

[0088] As mentioned above, in various embodiments of the present invention, the model AM may include or consist of a morphological model of the target anatomy, indicating at least one of its shape, size, and optionally its typical location, as described above. The morphological model AM may be a generic model or a patient-specific model (e.g., in the latter case, the model may have been obtained using a mapping medical device 41 associated with the system 300 in the manner described above with reference to FIGS. 3A and 3B). In some embodiments, the morphological model AM also further includes texture data, including, for example, spectral information indicating the appearance in an image of various tissues of the target anatomy.

[0089] Alternatively or additionally, the model AM retrieved by the model provider 313 may include or consist of a machine learning (ML) model trained for processing / recognition of the anatomical structure of interest in the image M in which it appears. As will be appreciated by those skilled in the art, such an ML model may be similar to the ML model described above with reference to Figures 3A and 3B.

[0090] In operation 430 (which may be performed, for example, by the model processor 314), the anatomical model AM is applied to one or more images M in which the target anatomical structure appears, and within those images, regions of interest ROI (e.g., groups of pixels / voxels) in which the target anatomical structure appears are respectively identified.

[0091] In this regard, it should be noted that operation 430 may be performed similarly to operation 230 described in detail above with reference to Figures 3A and 3B, but here applied to identifying ROIs within the captured image M itself. In this regard, in embodiments / cases in which the model AM is a morphological model, each ROI within the image M may be determined by fitting the model to the contents of the image M (e.g., in a manner similar to that described above with respect to fitting / mapping the model AM to the initial M in Figure 3A). Alternatively or additionally, in embodiments / cases in which the model AM is a machine learning (ML) model, the model AM may be operated on (fed with) each of the images M, thereby generating data indicative of each ROI within the image in which the subject's body anatomy appears.

[0092] In operation 440 (which may be performed, for example, by the rendering utility 318), one or more images M may be optimized by modifying volumetric properties such as gamma, brightness, sharpness, etc., and cropped to fit each ROI identified in operation 430. As will be appreciated by those skilled in the art, cropping may be performed by blanking / removing pixels / voxels in the image that are not part of the ROI. Thus, the cropped image M c is acquired, in which the target anatomy / body anatomy appears without (having removed) the surrounding tissue or other features.

[0093] Further, in optional operation 450, the system 300 (e.g., rendering utility 318) can render the cropped images to generate a desired 2D, 3D, and / or video presentation of the cropped subject's anatomy as it appears from various angles / perspectives and / or various 2D slices thereof, which can be displayed to the operator / physician 30 (e.g., via the UI 115).

[0094] To this end, as described above, the captured images M that are processed by the system 300 and from which cropped images are obtained may themselves be 2D, 3D / volume images or video sequences thereof. Thus, the images M and / or their cropped versions M c If M are 3D / volumetric images, operation 450 may be performed to render desired 2D slices of those cropped images. Alternatively or additionally, operation 450 may be performed to render 3D / volumetric images from desired viewpoints. Still additionally or alternatively, operation 450 may be performed to construct a video sequence of the target anatomy from these cropped images, whereby the video sequence may present a 3D video of the target anatomy isolated from the tissue surrounding the target anatomy, or a 2D video presenting a 2D slice / view of the target anatomy isolated from the surroundings of the target anatomy. After knowing the present invention, one skilled in the art will be able to use cropped images M to create 2D, 3D, or similar videos presented from various viewing angles, or to present various slices thereof. c 4. Those skilled in the art will readily appreciate the various rendering options that may be implemented by method operation 450 for rendering anatomical structures appearing in the image. [Example]

[0095] Example 1. A system for generating images of an anatomical structure, the system connectable to a catheter having a distal tip with an ultrasound imaging device capable of capturing volumetric images and a position sensor capable of providing position data indicative of the position of the imaging device. The system comprises one or more processors, the one or more processors: - processing position data of an ultrasound imaging device to determine a volumetric field of view (FOR) of the imaging device relative to the patient's body; providing a model depicting at least a portion of the anatomical structure present in the patient's body within said FOR; - a system configured and operable to adjust acquisition parameters of the ultrasound imaging device based on the model to optimize acquisition of the at least a portion of the body anatomical structure by the ultrasound imaging device while reducing visibility of surrounding tissue.

[0096] Example 2. The system of Example 1, wherein acquisition parameters of an ultrasound imaging device are adjusted based on a model to result in optimized acquisition of one or more separated volumetric images of at least a portion of a body anatomical structure with reduced appearance of surrounding tissue, and the system thereby acquires the one or more volumetric separated images and generates from the one or more volumetric separated images at least one of a 2D separated image, a 3D separated image, and a video sequence of 2D or 3D separated images of at least a portion of the body anatomical structure with reduced appearance of surrounding tissue.

[0097] Example 3. The system of Example 1 or 2, wherein the ultrasound imaging device is capable of capturing volumetric images of the patient's body up to a certain maximum field of view and maximum depth of field range, and the one or more processors are adapted to process position data of the ultrasound imaging device to determine an alignment between the particular maximum field of view and maximum depth of field range and the patient's body, thereby determining a volume FOR of the imaging device relative to the patient's body.

[0098] Example 4. The system of any one of Examples 1-3, wherein the system includes a user interface adapted to receive input data indicative of at least a portion of a body anatomical structure to be captured by the ultrasound imaging device.

[0099] Example 5. A system described in any one of Examples 1 to 4, wherein adjusting acquisition parameters of the ultrasound imaging device based on the model includes utilizing the model to determine a region of interest (ROI) within which at least a portion of the body anatomical structure resides in the ultrasound imaging device.

[0100] Example 6. The system of Example 5, wherein using the model to determine a region of interest (ROI) includes operating an ultrasound imaging device to acquire at least one initial image of at least a portion of the ROI, and determining an association between pixels / voxels in the at least one initial image and at least a portion of the body anatomical structure modeled by the model.

[0101] Example 7. The system of any one of Examples 1-6, wherein the model includes a morphological model showing at least one of the shape, size, and position of at least a portion of the body anatomy.

[0102] Example 8. Morphological model a generic model showing at least one of a characteristic shape, a characteristic size, and a characteristic location of at least a portion of a body anatomy; a patient-specific model illustrating at least one of the shape, size, and position of at least a portion of a body anatomy of the patient's body; a pathology-specific model that represents at least one of the shape, size, and location of at least a portion of a body anatomical structure having a particular pathology; and -Data indicating one or more characteristics of one or more tissue types present in at least a portion of the body anatomical structure.

[0103] Example 9. Association determining the fit between the locations of different regions of the body anatomy in the morphological model and the corresponding pixels / voxels of the initial image; and - Determining a match between tissue properties represented in the model for different regions of the body anatomy and spectral data of corresponding pixels / voxels.

[0104] Example 10. A system described in any one of Examples 6 to 9, wherein the model includes a machine learning model trained for recognition of a body anatomical structure in an image in which the body anatomical structure appears, and the association is determined by use of the model to recognize the body anatomical structure in an initial image.

[0105] Example 11. Adjusting acquisition parameters includes adjusting one or more of the following acquisition parameters of an imaging device to optimize acquisition of a region of interest (ROI) within a FOR that is occupied by at least a portion of a body anatomical structure: - adjusting a field of view (FOV) of an acquiring ultrasound imaging device to suppress acquisition of areas located to the side of at least a portion of the body anatomy; adjusting the depth of field (DOF) of an ultrasound imaging device to suppress capture of regions of the body anatomy located anterior and / or posterior to the ultrasound imaging device; - adjusting at least one of the gain of the ultrasound imaging device and its active illumination intensity according to at least one of the position or distance of the body anatomical structure relative to the ultrasound imaging device and the tissue type included in the body anatomical structure; - adjusting the frequency of active illumination of the ultrasound imaging device, thereby controlling the penetration depth of the active illumination (the penetration of illumination through the body tissue) according to the position of the body anatomical structure relative to the imaging device; - adjusting a gating time between active illumination and image sensing by the ultrasound imaging device to control the span of the DOF for the imaging device according to the position of the body anatomy relative to the ultrasound imaging device; -Adjusting the frame / scan rate of the ultrasound imaging device according to the motion characteristics of the body anatomy to accommodate accurate capture of moving anatomy.

[0106] Example 12. The system described in any one of Examples 2 to 11, wherein the one or more processors are further adapted to crop at least one image of the volumetric separated image, the 2D separated image, the 3D separated image, and the video sequence of the 2D or 3D separated images based on the model, and cropping the at least one image includes utilizing the model to determine associations between voxels or pixels of the image and at least a portion of the body anatomical structure, and removing or blanking voxels or pixels of the at least one image that are not associated with at least a portion of the body anatomical structure, thereby obtaining at least one cropped image of the body anatomical structure in which pixels or voxels not associated with the body anatomical structure have been removed or reduced.

[0107] Example 13. A system as described in any one of Examples 2 to 12, comprising at least twelve medical devices having position sensors and adapted to map at least a portion of the body anatomy of a patient's body, wherein one or more processors of the system are adapted to track the position of the at least one medical device and record the tracked position associated with the body anatomy, thereby constructing a patient-specific morphological model of at least a portion of the patient's body anatomy.

[0108] Example 14. The patient-specific morphological model is formed by the recorded tracking positions and includes a point cloud that indicates the shape of at least a portion of the patient's body anatomy; and -The system described in Example 13, wherein the medical device is at least one of: comprising one or more sensors adapted to sense one or more tissue properties of at least a portion of the patient's body anatomical structure at the tracking location.

[0109] Example 15. A system described in any one of Examples 2 to 14, adapted to generate a video of at least a portion of a body anatomical structure separated from surrounding tissue, wherein generating the video comprises processing a plurality of volumetric images acquired during successive time frames to generate therefrom a plurality of or corresponding separated or further cropped images, which are 2D or 3D images, thereby obtaining a video sequence of 2D or 3D images of at least a portion of a body anatomical structure of a patient's body, substantially freed of body tissue not associated with the body anatomical structure.

[0110] Example 16. A method for generating an image of an anatomical structure, the method comprising: obtaining position data from a catheter having a distal tip with an ultrasound imaging device capable of capturing volumetric images and a position sensor providing the position data indicative of a position of the ultrasound imaging device; processing the position data to determine a volumetric field of view (FOR) of the ultrasound imaging device relative to the patient's body; providing a model depicting at least a portion of the body anatomy present on the patient's body within the FOR; and adjusting capture parameters of the ultrasound imaging device based on the model to optimize capture of at least a portion of the body anatomy by the ultrasound imaging device while reducing the appearance of surrounding tissue.

[0111] Example 17. The method of Example 16, further comprising: acquiring at least one volumetric separation image captured by an ultrasound imaging device using acquisition parameters adjusted such that at least a portion of a body anatomical structure appears substantially separated from body tissue not associated with at least a portion of the body anatomical structure; and processing the at least one volumetric separation image to generate at least one of a 2D separation image, a 3D separation image, and a video sequence of 2D or 3D separation images of at least a portion of the body anatomical structure.

[0112] Example 18. The method of any one of Examples 16 or 17, wherein the ultrasound imaging device is capable of capturing volumetric images of the patient's body up to a specified maximum field of view and maximum depth of field range, and the method includes processing position data of the imaging device to determine alignment between the specified maximum field of view and maximum depth of field range and the patient's body, thereby determining a volume FOR of the imaging device relative to the patient's body.

[0113] Example 19. The method of any one of Examples 16 or 18, comprising receiving input data from a user interface indicative of at least a portion of a body anatomical structure to be captured by the ultrasound imaging device.

[0114] Example 20. The method of any one of Examples 16 or 19, wherein adjusting the acquisition parameters of the ultrasound imaging device based on the model includes utilizing the model to determine a region of interest (ROI) in which at least a portion of the body anatomical structure is present within the FOR of the imaging device.

[0115] Example 21. The method of Example 20, wherein using the model to determine a region of interest (ROI) includes operating an ultrasound imaging device to acquire at least one initial image of at least a portion of the FOR and determining an association between pixels / voxels in the at least one initial image and at least a portion of the body anatomical structure modeled by the model.

[0116] Example 22. The model is a morphological model representing at least one of the shape, size, and position of at least a portion of the body anatomy, the association being determined based on a match between the positions of different regions of the body anatomy in the morphological model and corresponding pixels / voxels of the initial image; and -A machine learning model trained for recognizing a body anatomical structure in an image in which the body anatomical structure appears, wherein the association is determined by using the model to recognize the body anatomical structure in an initial image.

[0117] Example 23. Adjusting acquisition parameters includes adjusting one or more of the following acquisition parameters of the imaging device to optimize acquisition of a region of interest (ROI) within a FOR that is occupied by at least a portion of a body anatomical structure: - adjusting a field of view (FOV) of an imaging device performing the capture to suppress capture of areas located to the sides of at least a portion of the body anatomy; adjusting the depth of field (DOF) of the imaging device to suppress capture of areas of the body anatomy that are located in front of and / or behind the imaging device; - adjusting at least one of the gain of the imaging device and its active illumination intensity according to at least one of the position or distance of the body anatomical structure relative to the imaging device and the tissue type included in the body anatomical structure; - adjusting the frequency of the active illumination used by the imaging device, thereby controlling the penetration depth of the active illumination according to the position of the body anatomy relative to the imaging device; - adjusting a gating time between active illumination and image sensing by the imaging device to control the span of DOF for the imaging device according to the position of the body anatomy relative to the imaging device; -Adjusting the frame rate / scan rate of the imaging device according to the motion characteristics of the body anatomical structures to accommodate accurate capture of moving anatomical structures.

[0118] Example 24. The method of any one of Examples 17 to 23, wherein the method further includes cropping at least one of the volumetric separated image, the 2D separated image, the 3D separated image, and the image of the video sequence of 2D or 3D separated images based on the model, and cropping at least one of the images includes utilizing the model to determine associations between voxels or pixels of the image and at least a portion of the body anatomical structure, and removing or blanking at least one voxel or pixel of the image that is not associated with at least a portion of the body anatomical structure to generate at least one cropped image of the body anatomical structure with pixels or voxels not associated with the body anatomical structure removed or reduced.

[0119] Example 25. The method of any one of Examples 16 to 24, further comprising constructing a patient-specific morphological model of at least a portion of the patient's body anatomy, wherein the constructing comprises tracking the position of at least one medical device having a position sensor thereon and adapted to map at least a portion of the patient's body anatomy, and recording the tracked position of the medical device at a position associated with the body anatomy, thereby constructing a patient-specific morphological model having a cloud point of at least a portion of the patient's body anatomy.

[0120] Example 25. A system for generating images of an anatomical structure. The system is adapted to receive images captured by a catheter having a distal tip with an imaging device capable of capturing images from within a patient's body and a position sensor capable of providing position data indicative of a position of the imaging device. The system includes one or more processors, the one or more processors: - obtaining at least one image captured by an imaging device and position data indicative of the position of the imaging device within the patient's body when the at least one image was obtained; - utilizing the position data to determine an area captured by the at least one image relative to the patient's body and to determine at least a portion of the subject's body anatomy present in the captured area; -Providing a model of body anatomy; - cropping at least one image based on a model, whereby the cropping includes utilizing the model to determine associations between voxels or pixels of the image and at least a portion of the body anatomy, and removing or blanking voxels or pixels of the at least one image that are not associated with at least a portion of the body anatomy to generate at least one cropped image of the body anatomy having pixels or voxels not associated with the body anatomy removed or reduced.

[0121] Example 26. the imaging device comprises an ultrasound imaging device; and -The system described in Example 25, wherein the imaging device is adapted to capture volumetric images from within the patient's body, and at least one image is a volumetric image captured by the imaging device.

[0122] Example 27. A system described in any one of Examples 25 or 26, wherein the system includes a user interface adapted to receive input data indicating at least a portion of a body anatomical structure to be presented in the cropped image.

[0123] Example 28. A system described in any one of Examples 25 to 27, wherein the model includes a morphological model showing at least one of the shape, size, and position of at least a portion of a body anatomical structure.

[0124] Example 29. Morphological model a generic model showing at least one of a characteristic shape, a characteristic size, and a characteristic location of at least a portion of a body anatomy; and - a patient-specific model illustrating at least one of the shape, size, and position of at least a portion of the body anatomy of the patient's body. - The system of Example 28, wherein the morphological model includes data indicative of one or more characteristics of one or more tissue types present in at least a portion of the body anatomy.

[0125] Example 30. The association between voxels or pixels of at least one image and at least a portion of a body anatomical structure is - determining a match between the locations of different regions of the body anatomy in the model and corresponding voxels of at least one image; - Determining a match between tissue properties represented in the model for different regions of the body anatomy and spectral data of corresponding voxels.

[0126] Example 31. A system described in any one of Examples 25 to 30, wherein the model includes a machine learning model trained for recognition of a body anatomical structure in images in which the body anatomical structure appears, and the association is determined by use of the model to recognize the body anatomical structure in at least one image.

[0127] Example 32. A system described in any one of Examples 25 to 31, adapted to generate a cropped video of at least a portion of the body anatomy, wherein pixels / voxels representing tissue surrounding at least a portion of the body anatomy are blanked or removed from the cropped video, and generating the video includes operating one or more processors to process a plurality of images acquired during successive time frames to generate therefrom a video sequence including a corresponding plurality of cropped images representing at least a portion of the patient's body anatomy substantially free of unassociated body tissue.

[0128] Example 33. A system described in any one of Examples 32, wherein the image is a 3D / volumetric image and the one or more processors are adapted to generate a cropped 3D / volumetric video presenting at least a portion of the body anatomical structure.

[0129] Example 34. A method for generating an image of an anatomical structure, the method comprising: obtaining at least one image captured by a catheter having a distal tip with an imaging device capable of capturing images from within the patient's body and a position sensor capable of providing position data indicative of the position of the imaging device; obtaining position data indicative of a position of the imaging device within the patient's body when the at least one image was captured; utilizing the position data to determine an area captured by the at least one image relative to the patient's body; determining at least a portion of a subject's body anatomy present in the captured region; Providing a model of body anatomy; 1. A method comprising: cropping at least one image based on a model, wherein cropping comprises utilizing the model to determine associations between voxels or pixels of the image and at least a portion of the body anatomy; and removing or blanking voxels or pixels of the at least one image that are not associated with at least a portion of the body anatomy to generate at least one cropped image of the body anatomy having pixels or voxels not associated with the body anatomy removed or reduced.

[0130] Example 35. the imaging device comprises an ultrasound imaging device; and - The method of Example 34, wherein the imaging device is adapted to capture volumetric images from within the patient's body, and at least one image is a volumetric image captured by the imaging device.

[0131] Example 36. The method of Example 34 or 35, wherein the method includes receiving input data from a user interface indicating at least a portion of the body anatomical structure to be presented in the cropped image.

[0132] Example 37. The method of any one of Examples 34 to 36, wherein the model comprises a morphological model showing at least one of the shape, size, and position of at least a portion of the body anatomical structure.

[0133] Example 38. Morphological model a generic model showing at least one of a characteristic shape, a characteristic size, and a characteristic location of at least a portion of a body anatomy; and - a patient-specific model illustrating at least one of the shape, size, and position of at least a portion of the body anatomy of the patient's body. The method of example 37, wherein the morphological model comprises data indicative of one or more characteristics of one or more tissue types present in at least a portion of the body anatomy.

[0134] Example 39. The association between voxels or pixels of at least one image and at least a portion of a body anatomical structure is - determining a match between the locations of different regions of the body anatomy in the model and corresponding voxels of at least one image; - Determining a match between tissue properties represented in the model for different regions of the body anatomy and spectral data of corresponding voxels.

[0135] Example 40. The method of any one of Examples 34 to 39, wherein the model includes a machine learning model trained for recognition of a body anatomical structure in images in which the body anatomical structure appears, and the association is determined by use of the model to recognize the body anatomical structure in at least one image.

[0136] Example 41. The method of any one of Examples 34-40, wherein the method includes generating a cropped video of at least a portion of the body anatomy, wherein pixels / voxels representing tissue surrounding at least a portion of the body anatomy are blanked or removed from the cropped video. Generating the video includes processing a plurality of images captured by the imaging device over successive time frames to generate therefrom a video sequence including a corresponding plurality of cropped images representing at least a portion of the patient's body anatomy substantially free of unrelated body tissue.

[0137] Example 42. The method of example 40, wherein the image is a 3D / volume image and the method is adapted to generate the cropped video as a 3D / volume video presenting at least a portion of the body anatomy.

[0138] Although the foregoing detailed description sets forth numerous specific details to provide a thorough understanding of the present invention, it will be apparent to those skilled in the art that the present invention may be practiced without these specific details. In other instances, well-known components, imaging devices, circuits, control logic, and details of computer program instructions for conventional algorithms and processes have not been shown in detail in order to avoid unnecessarily obscuring the present invention.

[0139] Software programming code embodying aspects of the present invention is typically maintained in permanent storage, such as a tangible computer-readable medium. In a client-server environment, such software programming code may be stored on either the client or the server. The software programming code may be embodied in any of a variety of known media for use with data processing systems, including, but not limited to, magnetic and optical storage devices such as disk drives, magnetic tape, compact discs (CDs), and digital video discs (DVDs), as well as computer instruction signals embodied in a transmission medium, with or without a carrier wave upon which the signal is modulated. For example, the transmission medium may include a communications network such as the Internet. Additionally, while some aspects of the present invention may be embodied in computer software, the functionality required to implement the present invention may alternatively be embodied, in part or entirely, using hardware components, such as application-specific integrated circuits or other hardware, or some combination of hardware components and software.

[0140] [Embodiment] (1) A system for generating images of an anatomical structure, the system being connectable to a catheter having a distal tip with an ultrasound imaging device capable of capturing volumetric images and a position sensor capable of providing position data indicative of a position of the imaging device, the system comprising one or more processors, the one or more processors: processing the position data of the ultrasound imaging device to determine a volumetric field of view (FOR) of the imaging device relative to the patient's body; providing a model representing at least a portion of a body anatomical structure present in the patient's body within the FOR; and a system configured and operable to adjust capture parameters of the ultrasound imaging device based on the model to optimize capture of the at least a portion of the body anatomical structure by the ultrasound imaging device while reducing the appearance of surrounding tissue. (2) The system described in embodiment 1, wherein the acquisition parameters of the ultrasound imaging device are adjusted based on the model to result in optimized acquisition of one or more separated volumetric images of at least a portion of the body anatomical structure with reduced appearance of surrounding tissue, and the system thereby acquires the one or more volumetric separated image acquisition devices and generates from the one or more volumetric separated image acquisition devices at least one of a 2D separated image, a 3D separated image, and a video sequence of 2D or 3D separated images of at least a portion of the body anatomical structure with reduced appearance of the surrounding tissue. (3) The system described in embodiment 1, comprising a user interface adapted to receive input data indicative of at least a portion of the body anatomical structure captured by the ultrasound imaging device. (4) The system described in embodiment 1, wherein adjusting the acquisition parameters of the ultrasound imaging device based on the model includes utilizing the model to determine a region of interest (ROI) within which at least a portion of the body anatomical structure resides within the FOR of the imaging device. (5) The system of embodiment 4, wherein using the model to determine the region of interest (ROI) includes operating the ultrasound imaging device to acquire at least one initial image of at least a portion of the FOR and determining an association between pixels / voxels in the at least one initial image and at least a portion of the body anatomical structure modeled by the model.

[0141] (6) The system of embodiment 1, wherein the model includes a morphological model that indicates at least one of the shape, size, and position of the at least part of the body anatomical structure. (7) The morphological model is a generic model showing at least one of a characteristic shape, a characteristic size, and a characteristic location of said at least one portion of said body anatomical structure; a patient-specific model representing at least one of a shape, a size, and a position of the at least part of the body anatomy of the patient's body; and - a pathology-specific model that indicates at least one of a shape, a size, and a position of the at least part of the body anatomical structure having a particular pathology; -The system of embodiment 6, wherein the morphological model includes data indicative of one or more characteristics of one or more tissue types present in at least the portion of the body anatomical structure. (8) The said association is: - determining a match between the locations of different regions of the body anatomy in the morphological model and the corresponding pixels / voxels of the initial image; and - determining a match between tissue properties represented in the model for different regions of the body anatomy and the spectral data of the corresponding pixels / voxels. (9) The system of embodiment 5, wherein the model includes a machine learning model trained for recognition of the body anatomical structure in an image in which the body anatomical structure appears, and the association is determined by use of the model to recognize the body anatomical structure in the initial image. (10) The adjustment of the acquisition parameters includes: adjusting one or more of the following acquisition parameters of the ultrasound imaging device to optimize acquisition of a region of interest (ROI) within the FOR occupied by the at least a portion of the body anatomical structure: adjusting a field of view (FOV) of the ultrasound imaging device performing the acquisition to suppress acquisition of areas located to the sides of the at least a portion of the body anatomical structure; adjusting a depth of field (DOF) of the ultrasound imaging device to suppress capture of regions anterior and / or posterior to the body anatomical structure relative to the ultrasound imaging device; - adjusting at least one of the gain of the imaging device and its active illumination intensity according to at least one of the position or distance of the body anatomical structure relative to the ultrasound imaging device and the tissue type contained in the body anatomical structure; - adjusting the frequency of active illumination used by the ultrasound imaging device, thereby controlling the penetration depth of the active illumination according to the position of the body anatomy relative to the imaging device; - adjusting a gating time between the active illumination and image sensing by the ultrasound imaging device to control the span of the DOF relative to the imaging device according to the position of the body anatomical structure relative to the ultrasound imaging device; -adjusting the frame rate / scan rate of the ultrasound imaging device according to the motion characteristics of the body anatomical structure to accommodate accurate capture of the moving anatomical structure.

[0142] (11) The system of embodiment 2, wherein the one or more processors are further adapted to crop at least one image of the volumetric separation image, the 2D separation image, the 3D separation image, and the video sequence of 2D or 3D separation images based on the model, and cropping the at least one image includes utilizing the model to determine associations between voxels or pixels of the image and the at least a portion of the body anatomical structure, and removing or blanking voxels or pixels of the at least one image that are not associated with the at least a portion of the body anatomical structure, thereby obtaining at least one cropped image of the body anatomical structure in which pixels or voxels not associated with the body anatomical structure have been removed or reduced. (12) The system described in embodiment 1, comprising at least one medical device having a position sensor and adapted to map the at least a portion of the body anatomy of the patient's body, wherein the one or more processors of the system are adapted to track the position of the at least one medical device and record the tracked position associated with the body anatomy, thereby constructing a patient-specific morphological model of the at least a portion of the body anatomy of the patient. (13) - the patient-specific morphological model includes a point cloud formed by the tracked locations and indicative of the shape of the at least part of the patient's body anatomy; and -The system described in embodiment 12, wherein the medical device is equipped with one or more sensors adapted to sense one or more tissue properties of at least a portion of the patient's body anatomical structure at the tracking location. (14) The system of embodiment 2, wherein the system is adapted to generate a video of the at least a portion of the body anatomical structure separated from surrounding tissue, and wherein generating the video includes operating the one or more processors to process a plurality of volumetric images acquired during successive time frames to generate therefrom a plurality of or corresponding separated or further cropped images, which are 2D or 3D images, thereby obtaining a video sequence of 2D or 3D images of the at least a portion of the body anatomical structure of the patient's body substantially free of body tissue unrelated to the body anatomical structure. (15) A method for generating an image of an anatomical structure, the method comprising: acquiring position data from a catheter having a distal tip comprising an ultrasound imaging device capable of capturing volumetric images and a position sensor providing the position data indicative of a position of the ultrasound imaging device; processing the position data to determine a volumetric field of view (FOR) of the ultrasound imaging device relative to the patient's body; providing a model representing at least a portion of a body anatomical structure present in the patient's body within the FOR; adjusting acquisition parameters of the ultrasound imaging device based on the model to optimize acquisition of the at least a portion of the body anatomy by the ultrasound imaging device while reducing the appearance of surrounding tissue; an imaging device.

[0143] (16) The method of embodiment 15, further comprising: acquiring at least one volumetric separation image captured by the ultrasound imaging device with the acquisition parameters adjusted such that the at least a portion of the body anatomical structure appears substantially separated from body tissue not associated with the at least a portion of the body anatomical structure; and processing the at least one volumetric separation image to generate at least one of a 2D separation image, a 3D separation image, and a video sequence of 2D or 3D separation images of the at least a portion of the body anatomical structure. (17) The method of embodiment 15, wherein the ultrasound imaging device is capable of capturing volumetric images of the patient's body up to a specified maximum field of view and maximum depth of field range, and the method includes processing the position data of the imaging device to determine alignment between the specified maximum field of view and maximum depth of field range and the patient's body, thereby determining the volume FOR of the imaging device relative to the patient's body. (18) The method of embodiment 15, comprising receiving input data from a user interface indicative of the at least a portion of the body anatomical structure captured by the ultrasound imaging device. (19) The method of embodiment 15, wherein adjusting the acquisition parameters of the ultrasound imaging device based on the model includes utilizing the model to determine a region of interest (ROI) within which at least a portion of the body anatomical structure resides within the FOR of the imaging device. (20) The method of embodiment 19, wherein using the model to determine the region of interest (ROI) includes operating the ultrasound imaging device to acquire at least one initial image of at least a portion of the FOR, and determining an association between pixels / voxels in the at least one initial image and at least a portion of the body anatomical structure modeled by the model.

[0144] (21) The model is a morphological model representing at least one of the shape, size, and position of the at least part of the body anatomical structure, the association being determined based on a match between the positions of different regions of the body anatomical structure in the morphological model and corresponding pixels / voxels of the initial image; and - a machine learning model trained for recognition of the body anatomical structure in an image in which the body anatomical structure appears, wherein the association is determined by using the model to recognize the body anatomical structure in the initial image. (22) The adjusting of the acquisition parameters includes adjusting one or more of the following acquisition parameters of the imaging device to optimize acquisition of a region of interest (ROI) within the FOR occupied by the at least a portion of the body anatomical structure: adjusting a field of view (FOV) of the imaging device performing said capture to suppress capture of areas located to the sides of said at least a portion of said body anatomical structure; adjusting the depth of field (DOF) of the imaging device to suppress capture of areas located in front of and / or behind the body anatomical structure relative to the imaging device; - adjusting at least one of the gain of the imaging device and its active illumination intensity according to at least one of the position or distance of the body anatomical structure relative to the imaging device and the tissue type contained in the body anatomical structure; - adjusting the frequency of active illumination used by the imaging device, thereby controlling the penetration depth of the active illumination according to the position of the body anatomy relative to the imaging device; - adjusting a gating time between the active illumination and image sensing by the imaging device to control the span of the DOF relative to the imaging device according to the position of the body anatomical structure relative to the imaging device; -adjusting the frame rate / scan rate of the imaging device according to the motion characteristics of the body anatomical structure to accommodate accurate capture of the moving anatomical structure. (23) A system for generating images of an anatomical structure, the system adapted to receive images captured by a catheter having a distal tip with an imaging device capable of capturing images from within a patient's body and a position sensor capable of providing position data indicative of a position of the imaging device, the system comprising one or more processors, the one or more processors: obtaining at least one image captured by the imaging device and the position data indicative of the position of the imaging device within the patient's body at the time the at least one image was obtained; utilizing the position data to determine a region captured by the at least one image relative to the patient's body and to determine at least a portion of a body anatomy of a subject present in the captured region; providing a model of said body anatomy; and cropping the at least one image based on the model, the cropping including utilizing the model to determine associations between voxels or pixels of the image and the at least one portion of the body anatomy, and removing or blanking the voxels or pixels of the at least one image that are not associated with the at least one portion of the body anatomy to generate at least one cropped image of the body anatomy with removed or reduced pixels or voxels not associated with the body anatomy. (24) - the imaging device includes an ultrasound imaging device; and -The system described in embodiment 23, wherein the imaging device is adapted to capture a volumetric image from within the patient's body, and the at least one image is a volumetric image captured thereby. (25) The system of embodiment 23, comprising a user interface adapted to receive input data indicating at least a portion of the body anatomical structure to be presented in the cropped image.

[0145] (26) The system of embodiment 23, wherein the model includes a morphological model that indicates at least one of the shape, size, and position of the at least part of the body anatomical structure. (27) The morphological model is a generic model showing at least one of a characteristic shape, a characteristic size, and a characteristic location of the at least part of the body anatomy; and - a patient-specific model representing at least one of a shape, a size, and a position of the at least part of the body anatomy of the patient's body; - The system of embodiment 26, wherein the morphological model includes data indicative of one or more characteristics of one or more tissue types present in said at least a portion of said body anatomical structure. (28) The association between the voxels or pixels of the at least one image and the at least part of the body anatomical structure is - determining a match between the locations of different regions of the body anatomy in the model and corresponding voxels of the at least one image; - Determining a match between tissue properties represented in the model for different regions of the body anatomy and the spectral data of the corresponding voxels. (29) The system of embodiment 23, wherein the model includes a machine learning model trained for recognition of the body anatomical structure in images in which the body anatomical structure appears, and the association is determined by use of the model to recognize the body anatomical structure in the at least one image. (30) The system of embodiment 23, adapted to generate a cropped video of the at least a portion of the body anatomical structure, wherein pixels / voxels representing tissue surrounding the at least a portion of the body anatomical structure are blanked or removed from the cropped video, and wherein generating the video includes operating the one or more processors to process a plurality of images acquired during successive time frames to generate therefrom a video sequence including a corresponding plurality of cropped images representing the at least a portion of the body anatomical structure of the patient substantially freed of unassociated body tissue.

[0146] (31) The system of embodiment 30, wherein the image is a 3D / volumetric image and the one or more processors are adapted to generate a cropped 3D / volumetric video presenting the at least a portion of the body anatomical structure. (32) A method for generating an image of an anatomical structure, the method comprising: obtaining at least one image captured by a catheter having a distal tip with an imaging device capable of capturing images from within a patient's body and a position sensor capable of providing position data indicative of a position of the imaging device; obtaining position data indicative of the position of the imaging device within the patient's body when the at least one image was captured; utilizing the position data to determine an area captured by the at least one image relative to the patient's body; determining at least a portion of a subject's body anatomy present in the captured region; providing a model of said body anatomy; and cropping the at least one image based on the model, wherein the cropping includes utilizing the model to determine associations between voxels or pixels of the at least one image and the at least one portion of the body anatomy, and removing or blanking the voxels or pixels of the at least one image that are not associated with the at least one portion of the body anatomy to generate at least one cropped image of the body anatomy with removed or reduced pixels or voxels not associated with the body anatomy. (33) - the imaging device includes an ultrasound imaging device; and - The method of embodiment 32, wherein the imaging device is adapted to capture a volumetric image from within the patient's body, and the at least one image is a volumetric image captured thereby. (34) The method of embodiment 32, including receiving input data from a user interface indicative of the at least a portion of the body anatomical structure to be presented in the cropped image. (35) The method of embodiment 32, wherein the model includes a morphological model that indicates at least one of the shape, size, and position of the at least part of the body anatomical structure.

[0147] (36) The morphological model is a generic model showing at least one of a characteristic shape, a characteristic size, and a characteristic location of the at least part of the body anatomy; and - a patient-specific model representing at least one of a shape, a size, and a position of the at least part of the body anatomy of the patient's body; - The method described in embodiment 35, wherein the morphological model includes data indicative of one or more characteristics of one or more tissue types present in said at least a portion of said body anatomical structure. (37) The association between the voxels or pixels of the at least one image and the at least part of the body anatomical structure is - determining a match between the locations of different regions of the body anatomy in the model and corresponding voxels of the at least one image; - determining a match between tissue properties represented in the model for different regions of the body anatomy and the spectral data of the corresponding voxels. (38) The method of embodiment 32, wherein the model includes a machine learning model trained for recognition of the body anatomical structure in images in which the body anatomical structure appears, and the association is determined by use of the model to recognize the body anatomical structure in the at least one image. (39) The method of embodiment 32, comprising generating a cropped video of the at least a portion of the body anatomical structure, wherein pixels / voxels representing tissue surrounding the at least a portion of the body anatomical structure are blanked or removed from the cropped video, wherein generating the video comprises processing a plurality of images captured by the imaging device in successive time frames to generate therefrom a video sequence including a corresponding plurality of cropped images representing the at least a portion of the body anatomical structure of the patient with unrelated body tissue substantially removed. (40) The method of embodiment 39, wherein the image is a 3D / volume image and the method is adapted to generate the cropped video as a 3D / volume video presenting the at least a portion of the body anatomical structure.

Claims

1. 1. A system for generating images of an anatomical structure, the system being connectable to a catheter having a distal tip with an ultrasound imaging device capable of capturing volumetric images and a position sensor capable of providing position data indicative of a position of the imaging device, the system comprising one or more processors, the one or more processors comprising: processing the position data of the ultrasound imaging device to determine a volumetric field of view (FOR) of the imaging device relative to the patient's body; providing a model depicting at least a portion of the body anatomy present in the patient's body within the FOR; and a system configured and operable to adjust capture parameters of the ultrasound imaging device based on the model to optimize capture of the at least a portion of the body anatomical structure by the ultrasound imaging device while reducing the appearance of surrounding tissue.

2. 2. The system of claim 1, wherein the acquisition parameters of the ultrasound imaging device are adjusted based on the model to result in optimized acquisition of one or more separated volumetric images of the at least portion of the body anatomical structure with the appearance of surrounding tissue reduced, and the system thereby acquires the one or more volumetric separated image acquisition devices and generates from the one or more volumetric separated image acquisition devices at least one of 2D separated images, 3D separated images, and video sequences of 2D or 3D separated images of the at least portion of the body anatomical structure with the appearance of the surrounding tissue reduced.

3. The system of claim 1 , comprising a user interface adapted to receive input data indicative of the at least a portion of the body anatomy captured by the ultrasound imaging device.

4. 2. The system of claim 1, wherein the adjusting of the acquisition parameters of the ultrasound imaging device based on the model includes utilizing the model to determine a region of interest (ROI) within which the at least a portion of the body anatomical structure resides within the FOR of the imaging device.

5. 5. The system of claim 4, wherein utilizing the model to determine the region of interest (ROI) comprises: operating the ultrasound imaging device to acquire at least one initial image of at least a portion of the FOR; and determining an association between pixels / voxels in the at least one initial image and at least a portion of the body anatomical structure modeled by the model.

6. The system of claim 1 , wherein the model comprises a morphological model that indicates at least one of a shape, a size, and a position of the at least a portion of the body anatomy.

7. The morphological model is a generic model showing at least one of a characteristic shape, a characteristic size, and a characteristic location of said at least part of said body anatomy; a patient-specific model representing at least one of the shape, size, and position of the at least part of the body anatomy of the patient's body; and a pathology-specific model representing at least one of the shape, size and location of said at least part of said body anatomical structure having a particular pathology; The system of claim 6, wherein the morphological model includes data indicative of one or more characteristics of one or more tissue types present in the at least one portion of the body anatomy.

8. The association is - determining the match between the locations of different regions of the body anatomy in the morphological model and the corresponding pixels / voxels of the initial image; and - determining a match between tissue properties represented in the model for different regions of the body anatomy and the spectral data of the corresponding pixels / voxels.

9. 6. The system of claim 5, wherein the model comprises a machine learning model trained for recognition of the body anatomical structure in images in which the body anatomical structure appears, and the association is determined by use of the model to recognize the body anatomical structure in the initial image.

10. The adjustment of the capture parameters includes: adjusting one or more of the following acquisition parameters of the ultrasound imaging device to optimize acquisition of a region of interest (ROI) within the FOR occupied by the at least a portion of the body anatomy: - adjusting the field of view (FOV) of the ultrasound imaging device performing said acquisition to suppress acquisition of areas located to the sides of said at least a portion of said body anatomical structure; - adjusting the depth of field (DOF) of the ultrasound imaging device to suppress capture of regions located anterior and / or posterior to the body anatomical structure relative to the ultrasound imaging device; - adjusting at least one of the gain of the imaging device and its active illumination intensity according to at least one of the position or distance of the body anatomical structure relative to the ultrasound imaging device and the tissue type contained in the body anatomical structure; - adjusting the frequency of the active illumination used by the ultrasound imaging device, thereby controlling the penetration depth of the active illumination according to the position of the body anatomy relative to the imaging device; - adjusting a gating time between the active illumination and image sensing by the ultrasound imaging device to control the span of the DOF relative to the imaging device according to the position of the body anatomical structure relative to the ultrasound imaging device; - adjusting the frame rate / scan rate of the ultrasound imaging device according to the motion characteristics of the body anatomical structure to accommodate accurate capture of the moving anatomical structure.

11. 3. The system of claim 2, wherein the one or more processors are further adapted to crop at least one image of the volumetric separation image, the 2D separation image, the 3D separation image, and the video sequence of 2D or 3D separation images based on the model, wherein cropping the at least one image includes utilizing the model to determine associations between voxels or pixels of the image and the at least one portion of the body anatomical structure, and removing or blanking voxels or pixels of the at least one image that are not associated with the at least one portion of the body anatomical structure, thereby obtaining at least one cropped image of the body anatomical structure in which pixels or voxels not associated with the body anatomical structure have been removed or reduced.

12. 10. The system of claim 1, comprising at least one medical device having a position sensor and adapted to map the at least a portion of the body anatomy of the patient's body, wherein the one or more processors of the system are adapted to track a position of the at least one medical device and record the tracked position associated with the body anatomy, thereby constructing a patient-specific morphological model of the at least a portion of the body anatomy of the patient.

13. the patient-specific morphological model is formed by the tracked locations and includes a point cloud that describes the shape of the at least part of the patient's body anatomy; and The system of claim 12, wherein the medical device comprises at least one of: one or more sensors adapted to sense one or more tissue properties of the at least a portion of the patient's body anatomy at the tracking location.

14. 3. The system of claim 2, wherein the system is adapted to generate a video of the at least a portion of the body anatomical structure separated from surrounding tissue, wherein generating the video comprises operating the one or more processors to process a plurality of volumetric images acquired during successive time frames to generate therefrom a plurality of or corresponding separated or further cropped images, which are 2D or 3D images, thereby obtaining a video sequence of 2D or 3D images of the at least a portion of the body anatomical structure of the patient's body substantially free of body tissue not associated with the body anatomical structure.

15. 1. A method for generating an image of an anatomical structure, the method comprising: acquiring position data from a catheter having a distal tip comprising an ultrasound imaging device capable of capturing volumetric images and a position sensor providing the position data indicative of a position of the ultrasound imaging device; processing the position data to determine a volumetric field of view (FOR) of the ultrasound imaging device relative to the patient's body; providing a model representing at least a portion of the body anatomy present in the patient's body within the FOR; adjusting acquisition parameters of the ultrasound imaging device based on the model to optimize acquisition of the at least a portion of the body anatomy by the ultrasound imaging device while reducing the appearance of surrounding tissue; A method comprising:

16. 16. The method of claim 15, further comprising: acquiring at least one volumetric separation image captured by the ultrasound imaging device with the acquisition parameters adjusted such that the at least one portion of the body anatomical structure appears substantially separated from body tissue not associated with the at least one portion of the body anatomical structure; and processing the at least one volumetric separation image to generate at least one of a 2D separation image, a 3D separation image, and a video sequence of 2D or 3D separation images of the at least one portion of the body anatomical structure.

17. 16. The method of claim 15, wherein the ultrasound imaging device is capable of capturing volumetric images of the patient's body up to a specified maximum field of view and maximum depth of field range, the method including processing the position data of the imaging device to determine a registration between the specified maximum field of view and maximum depth of field range and the patient's body, thereby determining the volume FOR of the imaging device relative to the patient's body.

18. The method of claim 15 , comprising receiving input data from a user interface indicative of the at least a portion of the body anatomy to be captured by the ultrasound imaging device.

19. 16. The method of claim 15, wherein the adjusting of the acquisition parameters of the ultrasound imaging device based on the model includes utilizing the model to determine a region of interest (ROI) within which the at least a portion of the body anatomical structure lies within the FOR of the imaging device.

20. 20. The method of claim 19, wherein utilizing the model to determine the region of interest (ROI) comprises: operating the ultrasound imaging device to acquire at least one initial image of at least a portion of the FOR; and determining an association between pixels / voxels in the at least one initial image and at least a portion of the body anatomical structure modeled by the model.

21. The model is a morphological model representing at least one of the shape, size and position of said at least part of said body anatomical structure, said association being determined based on a match between said positions of different regions of said body anatomical structure in said morphological model and corresponding pixels / voxels of said initial image; and - a machine learning model trained for recognition of the physical anatomical structure in an image in which the physical anatomical structure appears, wherein the association is determined by using the model to recognize the physical anatomical structure in the initial image.

22. The adjustment of the acquisition parameters may include adjusting one or more of the following acquisition parameters of the imaging device to optimize acquisition of a region of interest (ROI) within the FOR occupied by the at least a portion of the body anatomy: - adjusting the field of view (FOV) of the imaging device performing said capture to suppress capture of areas located to the sides of said at least a portion of said body anatomical structure; - adjusting the depth of field (DOF) of the imaging device to suppress capture of areas located in front and / or behind the body anatomy relative to the imaging device; - adjusting at least one of the gain of the imaging device and its active illumination intensity according to at least one of the position or distance of the body anatomical structure relative to the imaging device and the tissue type contained in the body anatomical structure; - adjusting the frequency of the active illumination used by the imaging device, thereby controlling the penetration depth of the active illumination according to the position of the body anatomy relative to the imaging device; - adjusting a gating time between the active illumination and image sensing by the imaging device to control the span of the DOF for the imaging device according to the position of the body anatomical structure relative to the imaging device; - adjusting the frame rate / scan rate of the imaging device according to the motion characteristics of the body anatomy to accommodate accurate capture of the moving anatomy.

23. 1. A system for generating images of an anatomical structure, the system adapted to receive images captured by a catheter having a distal tip with an imaging device capable of capturing images from within a patient's body and a position sensor capable of providing position data indicative of a position of the imaging device, the system comprising one or more processors, the one or more processors comprising: obtaining at least one image captured by the imaging device and the position data indicative of the position of the imaging device within the patient's body at the time the at least one image was obtained; utilizing the position data to determine a region captured by the at least one image relative to the patient's body and to determine at least a portion of a subject's anatomical structure present in the captured region; providing a model of said body anatomy; and cropping the at least one image based on the model, the cropping comprising: utilizing the model to determine associations between voxels or pixels of the image and the at least one portion of the body anatomy; and removing or blanking the voxels or pixels of the at least one image that are not associated with the at least one portion of the body anatomy to generate at least one cropped image of the body anatomy with removed or reduced pixels or voxels not associated with the body anatomy.

24. - the imaging device comprises an ultrasound imaging device; and - the imaging device is adapted to capture a volumetric image from within the patient's body, and the at least one image is a volumetric image captured thereby.

25. 24. The system of claim 23, comprising a user interface adapted to receive input data indicative of at least a portion of the body anatomy to be presented in the cropped image.

26. 24. The system of claim 23, wherein the model comprises a morphological model that indicates at least one of a shape, a size, and a position of the at least a portion of the body anatomy.

27. The morphological model is a generic model showing at least one of a characteristic shape, a characteristic size, and a characteristic location of said at least one portion of said body anatomy; and a patient-specific model representing at least one of the shape, size and position of the at least part of the body anatomy of the patient's body; 27. The system of claim 26, wherein the morphological model includes data indicative of one or more characteristics of one or more tissue types present in the at least part of the body anatomy.

28. The association between the voxels or pixels of the at least one image and the at least part of the body anatomy is determined by: - determining a match between the locations of different regions of the body anatomy in the model and corresponding voxels of the at least one image; - determining a match between tissue properties represented in the model for different regions of the body anatomy and the spectral data of the corresponding voxels.

29. 24. The system of claim 23, wherein the model comprises a machine learning model trained for recognition of the physical anatomical structure in images in which the physical anatomical structure appears, and the association is determined by use of the model to recognize the physical anatomical structure in the at least one image.

30. 24. The system of claim 23, adapted to generate a cropped video of the at least portion of the body anatomy, wherein pixels / voxels representing tissue surrounding the at least portion of the body anatomy are blanked or removed from the cropped video, and wherein generating the video comprises operating the one or more processors to process a plurality of images acquired during successive time frames to generate therefrom a video sequence comprising a corresponding plurality of cropped images representing the at least portion of the patient's body anatomy substantially free of unassociated body tissue.

31. 31. The system of claim 30, wherein the image is a 3D / volumetric image, and the one or more processors are adapted to generate a cropped 3D / volumetric video presenting the at least a portion of the body anatomy.

32. 1. A method for generating an image of an anatomical structure, the method comprising: obtaining at least one image captured by a catheter having a distal tip with an imaging device capable of capturing images from within a patient's body and a position sensor capable of providing position data indicative of the position of the imaging device; obtaining position data indicative of the position of the imaging device within the patient's body when the at least one image was captured; utilizing the position data to determine an area captured by the at least one image relative to the patient's body; determining at least a portion of a subject's body anatomy present in the captured region; providing a model of said body anatomy; and cropping the at least one image based on the model, wherein the cropping comprises utilizing the model to determine associations between voxels or pixels of the at least one image and the at least one portion of the body anatomy, and removing or blanking the voxels or pixels of the at least one image that are not associated with the at least one portion of the body anatomy to generate at least one cropped image of the body anatomy with removed or reduced pixels or voxels not associated with the body anatomy.

33. - the imaging device comprises an ultrasound imaging device; and - the imaging device is adapted to capture volumetric images from within the patient's body, and the at least one image is a volumetric image captured thereby.

34. 33. The method of claim 32, comprising receiving input data from a user interface indicative of the at least a portion of the body anatomy to be presented in the cropped image.

35. 33. The method of claim 32, wherein the model comprises a morphological model that indicates at least one of a shape, a size, and a position of the at least a portion of the body anatomy.

36. The morphological model is a generic model showing at least one of a characteristic shape, a characteristic size, and a characteristic location of said at least one portion of said body anatomy; and a patient-specific model representing at least one of the shape, size and position of the at least part of the body anatomy of the patient's body; The method of claim 35, wherein the morphological model includes data indicative of one or more properties of one or more tissue types present in the at least part of the body anatomy.

37. The association between the voxels or pixels of the at least one image and the at least part of the body anatomy is determined by: - determining a match between the locations of different regions of the body anatomy in the model and corresponding voxels of the at least one image; - determining a match between tissue properties represented in the model for different regions of the body anatomy and the spectral data of the corresponding voxels.

38. 33. The method of claim 32, wherein the model comprises a machine learning model trained for recognition of the physical anatomical structure in images in which the physical anatomical structure appears, and the association is determined by use of the model to recognize the physical anatomical structure in the at least one image.

39. 33. The method of claim 32, comprising generating a cropped video of the at least portion of the body anatomy, wherein pixels / voxels representing tissue surrounding the at least portion of the body anatomy are blanked or removed from the cropped video, wherein generating the video comprises processing a plurality of images captured by the imaging device in successive time frames to generate therefrom a video sequence including a corresponding plurality of cropped images representing the at least portion of the patient's body anatomy substantially free of unrelated body tissue.

40. 40. The method of claim 39, wherein the image is a 3D / volumetric image, and the method is adapted to generate the cropped video as a 3D / volumetric video presenting the at least part of the body anatomy.

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