Systems and methods for long scan adjustment and anatomy tracking

Abstract

An imaging system according to at least one embodiment of the present disclosure includes: an image capture device; a processor coupled with the image capture device; and memory coupled with the processor and storing data thereon that, when executed by the processor, enable the processor to: initiate a long scan process for a patient anatomy using the image capture device; determine that at least some of the patient anatomy comprises a non-linear anomaly; implement a long scan adjustment that compensates for the non-linear anomaly; and output a final long scan image that depicts the patient anatomy including the non-linear anomaly.

Description

SYSTEMS AND METHODS FOR LONG SCAN ADJUSTMENT AND ANATOMYTRACKINGBACKGROUND

[0001] The present disclosure is generally directed to imaging, and relates more particularly to surgical imaging.

[0002] Surgical robots may assist a surgeon or other medical provider in carrying out a surgical procedure, or may complete one or more surgical procedures autonomously. Imaging may be used by a medical provider for diagnostic and / or therapeutic purposes. Patient anatomy can change over time, particularly following placement of a medical implant in the patient anatomy.BRIEF SUMMARY

[0003] Example aspects of the present disclosure include:

[0004] An imaging system according to at least one embodiment of the present disclosure comprises: an image capture device; a processor coupled with the image capture device; and memory coupled with the processor and storing data thereon that, when executed by the processor, enable the processor to: initiate a long scan process for a patient anatomy using the image capture device; determine that at least some of the patient anatomy comprises a non-linear anomaly; implement a long scan adjustment that compensates for the non-linear anomaly; and output a final long scan image that depicts the patient anatomy including the non-linear anomaly.

[0005] Any of the features herein, wherein the long scan adjustment comprises dynamically adjusting a path of the image capture device to capture the non-linear anomaly during the long scan process.

[0006] Any of the features herein, wherein the dynamically adjusting comprises: tracking a position of the patient anatomy; and adjusting, based on the tracking, a pose of the image capture device relative to the patient anatomy.

[0007] Any of the features herein, wherein the tracking the position of the patient anatomy comprises: capturing, at a first time, an image depicting a first portion of the patient anatomy and the non-linear anomaly; segmenting the image into at least two segments, a first segment including the first portion of the patient anatomy and a second segment including the non-linear anomaly;and predicting, based on the segmenting, a position of the non-linear anomaly relative to the image capture device at a second time.

[0008] Any of the features herein, wherein the image capture device comprises a radiation source and an imaging collimator disposed at least partially over the radiation source, and wherein the adjusting the pose of the image capture device comprises: changing, based on the predicted position of the non-linear anomaly at the second time, an orientation of the imaging collimator.

[0009] Any of the features herein, further comprising: capturing, at the second time, a second image depicting the non-linear anomaly.

[0010] Any of the features herein, wherein the long scan adjustment comprises: detecting an initial long scan image of the patient anatomy failed to capture the non-linear anomaly; capturing at least one additional image of the patient anatomy, wherein the at least one additional image includes the non-linear anomaly; and merging the at least one additional image with the initial long scan image to produce the final long scan image that depicts the patient anatomy including the nonlinear anomaly.

[0011] Any of the features herein, wherein the non-linear anomaly comprises a curvature of the patient anatomy.

[0012] Any of the features herein, wherein the non-linear anomaly comprises an anatomical element different from the patient anatomy.

[0013] Any of the features herein, wherein the merging further comprises: generating a panoramic image depicting the patient anatomy and the non-linear anomaly.

[0014] Any of the features herein, wherein the capturing the at least one additional image of the patient anatomy comprises: causing the image capture device to move into a position to capture the at least one additional image.

[0015] Any of the features herein, wherein the image capture device comprises at least one of an 0-arm and a C-arm.

[0016] Any of the features herein, wherein the final long scan image comprises a fluoroscopic image, and wherein the fluoroscopic image is rendered to a display.

[0017] A system according to at least one embodiment of the present disclosure comprises: a processor; and a memory storing data thereon that, when processed by the processor, enable the processor to: initiate a long scan process for a patient anatomy using an image capture device; determine that at least some of the patient anatomy comprises a non-linear anomaly; implement along scan adjustment that compensates for the non-linear anomaly; and output a final long scan image that depicts the patient anatomy including the non-linear anomaly.

[0018] Any of the features herein, wherein the long scan adjustment comprises dynamically adjusting a path of the image capture device to capture the non-linear anomaly during the long scan process.

[0019] Any of the features herein, wherein the dynamically adjusting comprises: tracking a position of the patient anatomy; and adjusting, based on the tracking, a pose of the image capture device relative to the patient anatomy.

[0020] Any of the features herein, wherein the tracking the position of the patient anatomy comprises: capturing, at a first time, an image depicting a first portion of the patient anatomy and the non-linear anomaly; segmenting the image into at least two segments, a first segment including the first portion of the patient anatomy and a second segment including the non-linear anomaly; and predicting, based on the segmenting, a position of the non-linear anomaly relative to the image capture device at a second time.

[0021] Any of the features herein, wherein the image capture device comprises a radiation source and an imaging collimator disposed at least partially over the radiation source, and wherein the adjusting the pose of the image capture device comprises: changing, based on the predicted position of the non-linear anomaly at the second time, an orientation of the imaging collimator.

[0022] Any of the features herein, further comprising: capturing, at the second time, a second image depicting the non-linear anomaly.

[0023] Any of the features herein, wherein the long scan adjustment comprises: detecting an initial long scan image of the patient anatomy failed to capture the non-linear anomaly; capturing at least one additional image of the patient anatomy, wherein the at least one additional image includes the non-linear anomaly; and merging the at least one additional image with the initial long scan image to produce the final long scan image that depicts the patient anatomy including the nonlinear anomaly.

[0024] Any of the features herein, wherein the non-linear anomaly comprises a curvature of the patient anatomy.

[0025] Any of the features herein, wherein the non-linear anomaly comprises an anatomical element different from the patient anatomy.

[0026] Any of the features herein, wherein the merging further comprises: generating a panoramic image depicting the patient anatomy and the non-linear anomaly.

[0027] Any of the features herein, wherein the capturing the at least one additional image of the patient anatomy comprises: causing the image capture device to move into a position to capture the at least one additional image.

[0028] Any of the features herein, wherein the final long scan image comprises a fluoroscopic image, and wherein the fluoroscopic image is rendered to a display.

[0029] A method according to at least one embodiment of the present disclosure comprises: initiating a long scan process for a patient anatomy; determining that at least some of the patient anatomy comprises a non-linear anomaly; implementing a long scan adjustment that compensates for the non-linear anomaly; and outputting a final long scan image that depicts the patient anatomy including the non-linear anomaly.

[0030] Any of the features herein, further comprising: dynamically adjusting a path of an image capture device to capture the non-linear anomaly during the long scan process.

[0031] Any of the features herein, further comprising: tracking a position of the patient anatomy; and adjusting, based on the tracking, a pose of the image capture device relative to the patient anatomy.

[0032] Any of the features herein, further comprising: capturing, at a first time, an image depicting a first portion of the patient anatomy and the non-linear anomaly; segmenting the image into at least two segments, a first segment including the first portion of the patient anatomy and a second segment including the non-linear anomaly; and predicting, based on the segmenting, a position of the non-linear anomaly relative to the image capture device at a second time.

[0033] Any of the features herein, further comprising: changing, based on the predicted position of the non-linear anomaly at the second time, an orientation of an imaging collimator.

[0034] Any of the features herein, further comprising: capturing, at the second time, a second image depicting the non-linear anomaly.

[0035] Any of the features herein, further comprising: detecting an initial long scan image of the patient anatomy failed to capture the non-linear anomaly; capturing at least one additional image of the patient anatomy, wherein the at least one additional image includes the non-linear anomaly; and merging the at least one additional image with the initial long scan image to produce the final long scan image that depicts the patient anatomy including the non-linear anomaly.

[0036] Any of the features herein, wherein the non-linear anomaly comprises a curvature of the patient anatomy.

[0037] Any of the features herein, wherein the non-linear anomaly comprises an anatomical element different from the patient anatomy.

[0038] Any of the features herein, further comprising: generating a panoramic image depicting the patient anatomy and the non-linear anomaly.

[0039] Any of the features herein, further comprising: causing an image capture device to move into a position to capture the at least one additional image.

[0040] Any of the features herein, further comprising: rendering the final long scan image to a display.

[0041] Any aspect in combination with any one or more other aspects.

[0042] Any one or more of the features disclosed herein.

[0043] Any one or more of the features as substantially disclosed herein.

[0044] Any one or more of the features as substantially disclosed herein in combination with any one or more other features as substantially disclosed herein.

[0045] Any one of the aspects / features / embodiments in combination with any one or more other aspects / features / embodiments .

[0046] Use of any one or more of the aspects or features as disclosed herein.

[0047] It is to be appreciated that any feature described herein can be claimed in combination with any other feature(s) as described herein, regardless of whether the features come from the same described embodiment.

[0048] The details of one or more aspects of the disclosure are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the techniques described in this disclosure will be apparent from the description and drawings, and from the claims.

[0049] The phrases “at least one”, “one or more”, and “and / or” are open-ended expressions that are both conjunctive and disjunctive in operation. For example, each of the expressions “at least one of A, B and C”, “at least one of A, B, or C”, “one or more of A, B, and C”, “one or more of A, B, or C” and “A, B, and / or C” means A alone, B alone, C alone, A and B together, A and C together, B and C together, or A, B and C together. When each one of A, B, and C in the above expressions refers to an element, such as X, Y, and Z, or class of elements, such as XI -Xn, Yl-Ym, and Zl-Zo, the phrase is intended to refer to a single element selected from X, Y, and Z, a combination of elements selected from the same class (e.g., XI and X2) as well as a combination of elements selected from two or more classes (e.g., Y 1 and Zo).

[0050] The term “a” or “an” entity refers to one or more of that entity. As such, the terms “a” (or “an”), “one or more” and “at least one” can be used interchangeably herein. It is also to be noted that the terms “comprising”, “including”, and “having” can be used interchangeably.

[0051] The preceding is a simplified summary of the disclosure to provide an understanding of some aspects of the disclosure. This summary is neither an extensive nor exhaustive overview of the disclosure and its various aspects, embodiments, and configurations. It is intended neither to identify key or critical elements of the disclosure nor to delineate the scope of the disclosure but to present selected concepts of the disclosure in a simplified form as an introduction to the more detailed description presented below. As will be appreciated, other aspects, embodiments, and configurations of the disclosure are possible utilizing, alone or in combination, one or more of the features set forth above or described in detail below.

[0052] Numerous additional features and advantages of the present disclosure will become apparent to those skilled in the art upon consideration of the embodiment descriptions provided hereinbelow.BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

[0053] The accompanying drawings are incorporated into and form a part of the specification to illustrate several examples of the present disclosure. These drawings, together with the description, explain the principles of the disclosure. The drawings simply illustrate preferred and alternative examples of how the disclosure can be made and used and are not to be construed as limiting the disclosure to only the illustrated and described examples. Further features and advantages will become apparent from the following, more detailed, description of the various aspects, embodiments, and configurations of the disclosure, as illustrated by the drawings referenced below.

[0054] Fig. 1A is a diagram of aspects of a system according to at least one embodiment of the present disclosure;

[0055] Fig. IB is a diagram of aspects of the system according to at least one embodiment of the present disclosure;

[0056] Fig. 1C is a block diagram of aspects of the system according to at least one embodiment of the present disclosure;

[0057] Fig. 2 A is a schematic depicting a lateral view of a patient according to at least one embodiment of the present disclosure;

[0058] Fig. 2B is a schematic depicting a lateral view of an initial long scan of the patient according to at least one embodiment of the present disclosure;

[0059] Fig. 2C is a schematic depicting a lateral view of the initial long scan and additional images of the patient according to at least one embodiment of the present disclosure;

[0060] Fig. 2D is a schematic depicting a lateral view of additional images of the patient according to at least one embodiment of the present disclosure;

[0061] Fig. 2E is a schematic depicting a lateral view of additional images of the patient based on tracked patient anatomy according to at least one embodiment of the present disclosure;

[0062] Fig. 2F is a schematic depicting a coronal view of an initial long scan and additional image of the patient according to at least one embodiment of the present disclosure;

[0063] Fig. 3 is a flowchart according to at least one embodiment of the present disclosure;

[0064] Fig. 4 is a flowchart according to at least one embodiment of the present disclosure; and

[0065] Fig. 5 is a flowchart according to at least one embodiment of the present disclosure.DETAILED DESCRIPTION

[0066] It should be understood that various aspects disclosed herein may be combined in different combinations than the combinations specifically presented in the description and accompanying drawings. It should also be understood that, depending on the example or embodiment, certain acts or events of any of the processes or methods described herein may be performed in a different sequence, and / or may be added, merged, or left out altogether (e.g., all described acts or events may not be necessary to carry out the disclosed techniques according to different embodiments of the present disclosure). In addition, while certain aspects of this disclosure are described as being performed by a single module or unit for purposes of clarity, it should be understood that the techniques of this disclosure may be performed by a combination of units or modules associated with, for example, a computing device and / or a medical device.

[0067] In one or more examples, the described methods, processes, and techniques may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored as one or more instructions or code on a computer-readable medium and executed by a hardware-based processing unit. Alternatively or additionally, functions may be implemented using machine learning models, neural networks, artificial neural networks,or combinations thereof (alone or in combination with instructions). Computer-readable media may include non-transitory computer-readable media, which corresponds to a tangible medium such as data storage media (e.g., RAM, ROM, EEPROM, flash memory, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer).

[0068] Instructions may be executed by one or more processors, such as one or more digital signal processors (DSPs), general purpose microprocessors (e.g., Intel Core i3, i5, i7, or i9 processors; Intel Celeron processors; Intel Xeon processors; Intel Pentium processors; AMD Ryzen processors; AMD Athlon processors; AMD Phenom processors; Apple A10 or 10X Fusion processors; Apple Al l, A12, A12X, A12Z, or A13 Bionic processors; or any other general purpose microprocessors), graphics processing units (e.g., Nvidia GeForce RTX 2000-series processors, Nvidia GeForce RTX 3000-series processors, AMD Radeon RX 5000-series processors, AMD Radeon RX 6000-series processors, or any other graphics processing units), application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry. Accordingly, the term “processor” as used herein may refer to any of the foregoing structure or any other physical structure suitable for implementation of the described techniques. Also, the techniques could be fully implemented in one or more circuits or logic elements.

[0069] Before any embodiments of the disclosure are explained in detail, it is to be understood that the disclosure is not limited in its application to the details of construction and the arrangement of components set forth in the following description or illustrated in the drawings. The disclosure is capable of other embodiments and of being practiced or of being carried out in various ways. Also, it is to be understood that the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting. The use of “including,” “comprising,” or “having” and variations thereof herein is meant to encompass the items listed thereafter and equivalents thereof as well as additional items. Further, the present disclosure may use examples to illustrate one or more aspects thereof. Unless explicitly stated otherwise, the use or listing of one or more examples (which may be denoted by “for example,” “by way of example,” “e.g.,” “such as,” or similar language) is not intended to and does not limit the scope of the present disclosure.

[0070] When using an intraoperative image device, the surgical staff may try to maximize the size of the image to increase the amount of information that they can see. Some measurements(e.g., spine alignments) are performed on images that are larger than the imaging device is capable of producing. With some imaging devices (e.g., an O-arm) it is possible to scan a long film (e.g., a pseudo-panoramic image) to increase the size of the image. However, the image may not contain all the desired information. For example, the spine of the patient may be scanned, but the pelvis and shoulders do not appear in the image. In some cases, due to the contour of the anatomy (e.g., the spine), a rectangularly shaped scan may not capture the whole spine.

[0071] According to at least one embodiment of the present disclosure, multiple scans and / or images may be connected into one large image. A scan of the spine may be captured, as well as images of the shoulder and / or pelvis, and the images of the shoulder and / or pelvis may be connected to the scan of the spine to create one large image with relevant data to make clinical decisions. The scans may comprise a lateral view of the patient and / or a coronal view of the patient.

[0072] According to at least one embodiment of the present disclosure, the spine may be tracked during a scan, and the imaging components may be repositioned accordingly. When the contour of the spine is tracked, the imaging components may use a collimator to only expose the section of the spine that is needed. In other words, the collimator may be adjusted such that other anatomical tissues around the spine are not imaged.

[0073] Embodiments of the present disclosure provide technical solutions to one or more of the problems of (1) long scans failing to depict non-linear portions of patient anatomy and (2) excessive radiation exposure when capturing surgical images.

[0074] Turning first to Figs. 1A-1C, aspects of a system 100 according to at least one embodiment of the present disclosure is shown. The system 100 may be used to initiate long scans of a patient, adjust imaging components to capture images of the patient, and generate long scans based on captured images of the patient; to control, pose, and / or otherwise manipulate a surgical mount system, a surgical arm, and / or surgical tools attached thereto; and / or carry out one or more other aspects of one or more of the methods disclosed herein. The system 100 comprises a computing device 102, one or more imaging devices 112, a robot 114, a navigation system 118, a database 130, and / or a cloud or other network 134. Systems according to other embodiments of the present disclosure may comprise more or fewer components than the system 100. For example, the system 100 may not include one or more components of the computing device 102, the database 130, and / or the cloud 134.

[0075] With reference to Fig. 1A, the imaging device 112 according to at least one embodiment of the present disclosure is shown. The imaging device 112 may be operable to image anatomical feature(s) (e.g., a bone, veins, tissue, etc.) and / or other aspects of patient anatomy to yield image data (e.g., image data depicting or corresponding to a bone, veins, tissue, etc.). “Image data” as used herein refers to the data generated or captured by an imaging device 112, including in a machine-readable form, a graphical / visual form, and in any other form. In various examples, the image data may comprise data corresponding to an anatomical feature of a patient 148, or to a portion thereof. The image data may be or comprise a preoperative image, an intraoperative image, a postoperative image, or an image taken independently of any surgical procedure. In some embodiments, a first imaging device 112 may be used to obtain first image data (e.g., a first image) at a first time, and a second imaging device 112 may be used to obtain second image data (e.g., a second image) at a second time after the first time. The imaging device 112 may be capable of taking a two-dimensional (2D) image or a three-dimensional (3D) image to yield the image data. The imaging device 112 may be or comprise, for example, an ultrasound scanner (which may comprise, for example, a physically separate transducer and receiver, or a single ultrasound transceiver), an 0-arm, a C-arm, a G-arm, or any other device utilizing X-ray-based imaging (e.g., a fluoroscope, a CT scanner, or other X-ray machine), a magnetic resonance imaging (MRI) scanner, an optical coherence tomography (OCT) scanner, an endoscope, a microscope, an optical camera, a thermographic camera (e.g., an infrared camera), a radar system (which may comprise, for example, a transmitter, a receiver, a processor, and one or more antennae), or any other imaging device 112 suitable for obtaining images of an anatomical feature of a patient 148. The imaging device 112 may be contained entirely within a single housing, or may comprise a transmitter / emitter and a receiver / detector that are in separate housings or are otherwise physically separated.

[0076] In some embodiments, the imaging device 112 may comprise more than one imaging device 112. For example, a first imaging device may provide first image data and / or a first image, and a second imaging device may provide second image data and / or a second image. In still other embodiments, the same imaging device may be used to provide both the first image data and the second image data, and / or any other image data described herein. The imaging device 112 may be operable to generate a stream of image data. For example, the imaging device 112 may be configured to operate with an open shutter, or with a shutter that continuously alternates betweenopen and shut so as to capture successive images. For purposes of the present disclosure, unless specified otherwise, image data may be considered to be continuous and / or provided as an image data stream if the image data represents two or more frames per second.

[0077] The imaging device 112 comprises an upper wall or member 152, a lower wall or member 160, and a pair of sidewalls or members 156A, 156B. In some embodiments, the imaging device 112 is fixed securable to an operating room wall 168 (such as, for example, a ground surface of an operating room or other room). In other embodiments, the imaging device 112 may be releasably securable to the operating room wall 168 or may be a standalone component that is simply supported by the operating room wall 168.

[0078] A table 150 configured to support the patient 148 may be positioned orthogonally to the imaging device 112, such that the table 150 extends in a first direction from the imaging device 112. In some embodiments, the table 150 may be mounted to the imaging device 112. In other embodiments, the table 150 may be releasably mounted to the imaging device 112. In still other embodiments, the table 150 may not be attached to the imaging device 112. In such embodiments, the table 150 may be supported and / or mounted to an operating room wall, for example. In embodiments where the table 150 is mounted to the imaging device 112 (whether detachably mounted or permanently mounted), the table 150 may be mounted to the imaging device 112 such that a pose of the table 150 relative to the imaging device 112 is selectively adjustable. The patient 148 may be positioned on the table 150 in a supine position, a prone position, a recumbent position, and the like.

[0079] The table 150 may be any operating table configured to support the patient 148 during a surgical procedure. The table 150 may include any accessories mounted to or otherwise coupled to the table 150 such as, for example, a bed rail, a bed rail adaptor, an arm rest, an extender, or the like. The table 150 may be stationary or may be operable to maneuver the patient 148 (e.g., the table 150 may be able to move). In some embodiments, the table 150 has two positioning degrees of freedom and one rotational degree of freedom, which allows positioning of the specific anatomy of the patient anywhere in space (within a volume defined by the limits of movement of the table 150). For example, the table 150 can slide forward and backward and from side to side, and can tilt (e.g., around an axis positioned between the head and foot of the table 150 and extending from one side of the table 150 to the other) and / or roll (e.g., around an axis positioned between the two sides of the table 150 and extending from the head of the table 150 to the foot thereof). In otherembodiments, the table 150 can bend at one or more areas (which bending may be possible due to, for example, the use of a flexible surface for the table 150, or by physically separating one portion of the table 150 from another portion of the table 150 and moving the two portions independently). In at least some embodiments, the table 150 may be manually moved or manipulated by, for example, a surgeon or other user, or the table 150 may comprise one or more motors, actuators, and / or other mechanisms configured to enable movement and / or manipulation of the table 150 by a processor such as a processor 104 of the computing device 102.

[0080] The imaging device 112 comprises a gantry. The gantry may be or comprise a substantially circular, or “O-shaped,” housing that enables imaging of objects placed into an isocenter thereof. In other words, the gantry may be positioned around the object being imaged. In some embodiments, the gantry may be disposed at least partially within the upper wall 152, the sidewalls 156A, 156B, and the lower wall 160 of the imaging device 112.

[0081] The imaging device 112 also comprises a source 138 and a detector 140. The source 138 may be a device configured to generate and emit radiation, and the detector 140 may be a device configured to detect the emitted radiation. In some embodiments, the source 138 and the detector 140 may be or comprise an imaging source and an imaging detector (e.g., the source 138 and the detector 140 are used to generate data useful for producing images). The source 138 may be positioned in a first position and the detector 140 may be positioned in a second position opposite the source 138. In some embodiments, the source 138 comprises an X-ray source such as, for example, a thermionic emission tube, a cold emission x-ray tube, or the like. The source 138 may project a radiation beam that passes through the patient 148 and onto the detector 140 located on the opposite side of the imaging device 112. The detector 140 may be or comprise one or more sensors that receive the radiation beam (e.g., once the radiation beam has passed through the patient 148) and transmit information related to the radiation beam to one or more other components of the system 100 for processing, such as to the processor 104.

[0082] In some embodiments, the detector 140 may comprise an array. For example, the detector 140 may comprise three 2D flat panel solid-state detectors arranged side-by-side, and angled to approximate the curvature of the imaging device 112. It will be understood, however, that various detectors and detector arrays can be used with the imaging device 112, including any detector configurations used in typical diagnostic fan-beam or cone-beam CT scanners. For example, thedetector 140 may comprise a 2D thin-film transistor X-ray detector using scintillator amorphous- silicon technology.

[0083] The source 138 may be or comprise a radiation tube (e.g., an x-ray tube) capable of generating the radiation beam. In some embodiments, the source 138 and / or the detector 140 may comprise a collimator 144 configured to confine or shape the radiation beam emitted from the source 138 and received at the detector 140. Once the radiation beam passes through patient tissue and received at the detector 140, the signals output from the detector 140 may be processed by the processor 104 to generate a reconstructed image of the patient tissue. In this way, the imaging device 112 can effectively generate reconstructed images of the patient tissue imaged by the source 138 and the detector 140.

[0084] The source 138 and the detector 140 may be attached to the gantry and configured to rotate 360 degrees around the patient 148 in a continuous or step-wise manner so that the radiation beam can be projected through the patient 148 at various angles. In other words, the source 138 and the detector 140 may rotate, spin, or otherwise revolve about an axis that passes through the top and bottom of the patient 148, with the patient anatomy that is the subject of the imaging positioned at the isocenter of the imaging device 112. The rotation may occur through a drive mechanism that causes the gantry to move such that the source 138 and the detector 140 encircle the patient 148 on the table 150. At each projection angle, the radiation beam passes through and is attenuated by the patient 148. The attenuated radiation is then detected by the detector 140. The detected radiation from each of the projection angles can then be processed, using various reconstruction techniques, to produce a 2D or 3D reconstruction image of the patient 148. For example, the processor 104 may be used to perform image processing 120 to generate the reconstruction image. Additionally or alternatively, the source 138 and the detector 140 may move along a length of the patient 148, as depicted in Fig. IB. For example, the table 150 holding the patient 148 may move in the direction of arrow 184 while the source 138 and detector 140 remain in a fixed location, such that the length of the patient can be scanned. In such embodiments, the scanned data may be used to generate one or more reconstructed images of the patient 148 and / or a long scan image of the patient 148.

[0085] The computing device 102 comprises a processor 104, a memory 106, a communication interface 108, and a user interface 110. Computing devices according to other embodiments of the present disclosure may comprise more or fewer components than the computing device 102.

[0086] The processor 104 of the computing device 102 may be any processor described herein or any similar processor. The processor 104 may be configured to execute instructions stored in the memory 106, which instructions may cause the processor 104 to carry out one or more computing steps utilizing or based on data received from the imaging device 112, the robot 114, the navigation system 118, the database 130, and / or the cloud 134.

[0087] The memory 106 may be or comprise RAM, DRAM, SDRAM, other solid-state memory, any memory described herein, or any other tangible, non-transitory memory for storing computer- readable data and / or instructions. The memory 106 may store information or data useful for completing, for example, any step of the methods 300, 400, and / or 500 described herein, or of any other methods. The memory 106 may store, for example, instructions and / or machine learning models that support one or more functions of the robot 114. For instance, the memory 106 may store content (e.g., instructions and / or machine learning models) that, when executed by the processor 104, enable image processing 120, segmentation 122, transformation 124, and / or registration 128. Such content, if provided as in instruction, may, in some embodiments, be organized into one or more applications, modules, packages, layers, or engines. Alternatively or additionally, the memory 106 may store other types of content or data (e.g., machine learning models, artificial neural networks, deep neural networks, etc.) that can be processed by the processor 104 to carry out the various method and features described herein. Thus, although various contents of memory 106 may be described as instructions, it should be appreciated that functionality described herein can be achieved through use of instructions, algorithms, and / or machine learning models. The data, algorithms, and / or instructions may cause the processor 104 to manipulate data stored in the memory 106 and / or received from or via the imaging device 112, the robot 114, the database 130, and / or the cloud 134.

[0088] The computing device 102 may also comprise a communication interface 108. The communication interface 108 may be used for receiving image data or other information from an external source (such as the imaging device 112, the robot 114, the navigation system 118, the database 130, the cloud 134, and / or any other system or component not part of the system 100), and / or for transmitting instructions, images, or other information to an external system or device (e.g., another computing device 102, the imaging device 112, the robot 114, the navigation system 118, the database 130, the cloud 134, and / or any other system or component not part of the system 100). The communication interface 108 may comprise one or more wired interfaces (e.g., a USBport, an Ethernet port, a Firewire port) and / or one or more wireless transceivers or interfaces (configured, for example, to transmit and / or receive information via one or more wireless communication protocols such as 802.11a / b / g / n, Bluetooth, NFC, ZigBee, and so forth). In some embodiments, the communication interface 108 may be useful for enabling the computing device 102 to communicate with one or more other processors 104 or computing devices 102, whether to reduce the time needed to accomplish a computing-intensive task or for any other reason.

[0089] The computing device 102 may also comprise one or more user interfaces 110. The user interface 110 may be or comprise a keyboard, mouse, trackball, monitor, television, screen, touchscreen, and / or any other device for receiving information from a user and / or for providing information to a user. The user interface 110 may be used, for example, to receive a user selection or other user input regarding any step of any method described herein. Notwithstanding the foregoing, any required input for any step of any method described herein may be generated automatically by the system 100 (e.g., by the processor 104 or another component of the system 100) or received by the system 100 from a source external to the system 100. In some embodiments, the user interface 110 may be useful to allow a surgeon or other user to modify instructions to be executed by the processor 104 according to one or more embodiments of the present disclosure, and / or to modify or adjust a setting of other information displayed on the user interface 110 or corresponding thereto.

[0090] Although the user interface 110 is shown as part of the computing device 102, in some embodiments, the computing device 102 may utilize a user interface 110 that is housed separately from one or more remaining components of the computing device 102. In some embodiments, the user interface 110 may be located proximate one or more other components of the computing device 102, while in other embodiments, the user interface 110 may be located remotely from one or more other components of the computer device 102.

[0091] The robot 114 may be any surgical robot or surgical robotic system. The robot 114 may be or comprise, for example, the Mazor X™ Stealth Edition robotic guidance system. The robot 114 may be configured to position the imaging device 112 at one or more precise position(s) and orientation(s), and / or to return the imaging device 112 to the same position(s) and orientation(s) at a later point in time. The robot 114 may additionally or alternatively be configured to manipulate a surgical tool (whether based on guidance from the navigation system 118 or not) to accomplish or to assist with a surgical task. In some embodiments, the robot 114 may be configured to holdand / or manipulate an anatomical element during or in connection with a surgical procedure. The robot 114 may comprise one or more robotic arms 116. In some embodiments, the robotic arm 116 may comprise a first robotic arm and a second robotic arm, though the robot 114 may comprise more than two robotic arms. In some embodiments, one or more of the robotic arms 116 may be used to hold and / or maneuver the imaging device 112. In embodiments where the imaging device 112 comprises two or more physically separate components (e.g., a transmitter and receiver), one robotic arm 116 may hold one such component, and another robotic arm 116 may hold another such component. Each robotic arm 116 may be positionable independently of the other robotic arm. The robotic arms 116 may be controlled in a single, shared coordinate space, or in separate coordinate spaces.

[0092] The robot 114, together with the robotic arm 116, may have, for example, one, two, three, four, five, six, seven, or more degrees of freedom. Further, the robotic arm 116 may be positioned or positionable in any pose, plane, and / or focal point. The pose includes a position and an orientation. As a result, an imaging device 112, surgical tool, or other object held by the robot 114 (or, more specifically, by the robotic arm 116) may be precisely positionable in one or more needed and specific positions and orientations.

[0093] The robotic arm(s) 116 may comprise one or more sensors that enable the processor 104 (or a processor of the robot 114) to determine a precise pose in space of the robotic arm 116 (as well as any object or element held by or secured to the robotic arm 116).

[0094] In some embodiments, reference markers (e.g., navigation markers) may be placed on the robot 114 (including, e.g., on the robotic arm 116), the imaging device 112, or any other object in the surgical space. The reference markers may be tracked by the navigation system 118, and the results of the tracking may be used by the robot 114 and / or by an operator of the system 100 or any component thereof. In some embodiments, the navigation system 118 can be used to track other components of the system (e.g., imaging device 112) and the system can operate without the use of the robot 114 (e.g., with the surgeon manually manipulating the imaging device 112 and / or one or more surgical tools, based on information and / or instructions generated by the navigation system 118, for example).

[0095] The navigation system 118 may provide navigation for a surgeon and / or a surgical robot during an operation. The navigation system 118 may be any now-known or future-developed navigation system, including, for example, the Medtronic StealthStation™ S8 surgical navigationsystem or any successor thereof. The navigation system 118 may include one or more cameras or other sensor(s) for tracking one or more reference markers, navigated trackers, or other objects within the operating room or other room in which some or all of the system 100 is located. The one or more cameras may be optical cameras, infrared cameras, or other cameras. In some embodiments, the navigation system 118 may comprise one or more electromagnetic sensors. In various embodiments, the navigation system 118 may be used to track a position and orientation (e.g., a pose) of the imaging device 112, the robot 114 and / or robotic arm 116, and / or one or more surgical tools (or, more particularly, to track a pose of a navigated tracker attached, directly or indirectly, in fixed relation to the one or more of the foregoing). The navigation system 118 may include a display for displaying one or more images from an external source (e.g., the computing device 102, imaging device 112, or other source) or for displaying an image and / or video stream from the one or more cameras or other sensors of the navigation system 118. In some embodiments, the system 100 can operate without the use of the navigation system 118. The navigation system 118 may be configured to provide guidance to a surgeon or other user of the system 100 or a component thereof, to the robot 114, or to any other element of the system 100 regarding, for example, a pose of one or more anatomical elements, whether or not a tool is in the proper trajectory, and / or how to move a tool into the proper trajectory to carry out a surgical task according to a preoperative or other surgical plan.

[0096] The database 130 may store information that correlates one coordinate system to another (e.g., one or more robotic coordinate systems to a patient coordinate system and / or to a navigation coordinate system). The database 130 may additionally or alternatively store, for example, one or more surgical plans (including, for example, pose information about a target and / or image information about a patient’s anatomy at and / or proximate the surgical site, for use by the robot 114, the navigation system 118, and / or a user of the computing device 102 or of the system 100); one or more images useful in connection with a surgery to be completed by or with the assistance of one or more other components of the system 100; and / or any other useful information. The database 130 may be configured to provide any such information to the computing device 102 or to any other device of the system 100 or external to the system 100, whether directly or via the cloud 134. In some embodiments, the database 130 may be or comprise part of a hospital image storage system, such as a picture archiving and communication system (PACS), a healthinformation system (HIS), and / or another system for collecting, storing, managing, and / or transmitting electronic medical records including image data.

[0097] The cloud 134 may be or represent the Internet or any other wide area network. The computing device 102 may be connected to the cloud 134 via the communication interface 108, using a wired connection, a wireless connection, or both. In some embodiments, the computing device 102 may communicate with the database 130 and / or an external device (e.g., a computing device) via the cloud 134.

[0098] The system 100 or similar systems may be used, for example, to carry out one or more aspects of any of the methods 300, 400, and / or 500 described herein. The system 100 or similar systems may also be used for other purposes.

[0099] With reference to Figs. 2A-2F, various schematics of lateral and coronal views depicting patient anatomy according to at least one embodiment of the present disclosure are shown.

[0100] Turning first to Fig. 2A, a lateral view 204 of the patient 148 is shown. A first image 208 of patient anatomy 212 may be captured by the imaging device 112. The first image 208 may depict a lateral view of the patient anatomy 212 through which the radiation beam generated by the source 138 and received by the detector 140 passes. In other words, the source 138 may be positioned in the right-hand side of the patient 148 while the detector 140 is positioned on the left-hand side of the patient 148 (or vice versa), such that the radiation beam passes through the patient anatomy 212 and into the detector 140. The data generated by the detector 140 based on the received radiation beam may then be used to generate the first image 208 (e.g., by the processor 104 using image processing 120).

[0101] In some embodiments, first image 208 may be extended into a long scan 216 by moving the source 138 and the detector 140 along a direction of the axis 206 running through the patient 148. In some embodiments, the direction of the axis 206 along which the source 138 and the detector 140 move may be the same direction as the direction indicated by the arrow 136. In some embodiments, the long scan 216 may be formed by moving the patient 148 relative to the source 138 and the detector 140. For example, the patient 148 may be positioned in a prone position on the table 150. The table 150 may then pass through an isocenter of the imaging device 112 while moving in the direction indicated by the arrow 136, such that the source 138 and the detector 140 generate projection data along a length of the patient 148. In some embodiments, the long scan 216 may be or comprise a fluoroscopic image.

[0102] With reference to Fig. 2B, the long scan 216 may capture only a portion of the patient anatomy 212 that lies along the axis 206, without imaging other portions of the patient anatomy 212. Such omissions may be due to non-linear anomalies resulting from the non-linear nature of the patient anatomy 212. Stated differently, the non-linear anomalies may correspond to the patient anatomy 212 that do not lie along the axis 206, and are thus missed when the source 138 and the detector 140 image the patient 148 to form the long scan 216. In some cases, an anatomical feature may be classified as a non-linear anomaly when the anatomical feature is not depicted in the long scan 216, when only a portion of the anatomical feature is depicted in the long scan 216 (e.g., another portion of the anatomical feature is not imaged by the imaging device 112 and does not appear in the long scan 216), and / or when an axis defining the direction in which the source 138 and the detector 140 move during the long scan process (e.g., axis 206) does not pass through anatomical feature.

[0103] The non-linear anomalies may arise due to the curvature of the patient anatomy 212. For example, the patient anatomy 212 may comprise the spine, which is curved. The curvature of the spine can result in the long scan 216 failing to capture a first non-linear anomaly 220 and a second non-linear anomaly 224 of the patient anatomy 212. The non-linear anomaly may be part of the natural shape of the patient anatomy 212, such as one or more vertebrae associated with the shoulder of the patient 148. Additionally or alternatively, the non-linear anomaly may be or comprise anatomical features proximate or adjacent to the patient anatomy 212 that may be beneficial or useful when included in the long scan 216, but are not captured by the long scan 216. One example of such a non-linear anomaly comprises the second non-linear anomaly 224, which may correspond to a hip or pelvis (or portion thereof) of the patient 148. It is to be understood that, while the first non-linear anomaly 220 and the second non-linear anomaly 224 are discussed herein, an additional or alternative number of non-linear anomalies may exist. Similarly, the present disclosure covers non-linear anomalies for other portions of patient anatomy other than the spine.

[0104] In some embodiments, the first non-linear anomaly 220 and / or the second non-linear anomaly 224 may comprise anatomical structures other than the patient anatomy 212. For example, the first non-linear anomaly 220 may be or comprise the shoulders of the patient 148. In another example, the second non-linear anomaly 224 may be or comprise the pelvis (or a portion thereof) of the patient 148. The shoulders and / or pelvis of the patient 148 may be identified and images thereof may be captured and integrated into a final long scan, as discussed in further detail below.

[0105] The first non-linear anomaly 220 and / or the second non-linear anomaly 224 may be identified by the processor 104 using, for example, image processing 120 and segmentation 122. For example, the processor 104 may use image processing 120 to generate a reconstructed image (e.g., the first image 208) from the data received from the detector 140, and then may use segmentation 122 to segment the first image 208 into a plurality of segments. The segments may correspond to the patient anatomy 212 depicted in the first image 208. The processor 104 may then determine whether the segments include the first non-linear anomaly 220 and / or the second nonlinear anomaly 224. When the patient anatomy 212 comprises the spine, for example, the first image 208 may depict vertebrae but not the second non-linear anomaly 224 (e.g., a portion of the hips or pelvis of the patient 148). The processor 104 may determine, based on the segmentation of the first image 208, that the second non-linear anomaly 224 has not been captured, and may instruct the imaging device 112 to capture an image depicting the second non-linear anomaly 224.

[0106] In some embodiments, the processor 104 may determine the locations of the first nonlinear anomaly 220 and / or the second non-linear anomaly 224 based on the known location of the patient anatomy 212. In some embodiments, the processor 104 may perform the determination before and / or during the long scan process. For example, the processor 104 may access the surgical plan from the database 130 and / or track the location of the imaging device 112 relative to the patient anatomy 212 to determine that the movement of the source 138 and the detector 140 along the axis 206 will result in the long scan 216 failing to include the first non-linear anomaly 220 and / or the second non-linear anomaly 224. In such embodiments, the processor 104 may notify the user (e.g., a surgeon) via the user interface 110, and may request user input regarding adjustments to the surgical plan to capture the first non-linear anomaly 220 and / or the second non-linear anomaly 224. For example, the processor 104 may recommend that one or more additional images of the patient anatomy 212 be captured that include the first non-linear anomaly 220 and / or the second non-linear anomaly 224. In some embodiments, the user may decline to capture the additional images of the patient anatomy 212, such as when the first non-linear anomaly 220 and / or the second non-linear anomaly 224 are not relevant to the surgery or surgical procedure, when the user does not wish to exposure the patient 148 to additional radiation, or for any other reason. In other embodiments, the user may accept the recommendation, and the processor 104 may cause the imaging device 112 to capture additional images of the patient anatomy 212.

[0107] With reference to Figs. 2C-2D, the additional images of the patient anatomy 212 may comprise a second image 228 and a third image 232. The second image 228 may depict the first non-linear anomaly 220, while the third image 232 may depict the second non-linear anomaly 224. The second image 228 and the third image 232 may be captured, for example, when it is desirable to expose the patient 148 to minimal radiation. Additionally or alternatively, the additional images may comprise a plurality of smaller images. For example, the imaging device 112 may capture image data that enables formation of a fourth image 236, a fifth image 240, a sixth image 244, and / or a seventh image 248. In such examples, the first non-linear anomaly 220 and / or the second non-linear anomaly 224 may be depicted in two or more of the additional images (e.g., there is overlap in image content between the fourth image 236 and the fifth image 240, there is overlap in image content between the fifth image 240 and the sixth image 244, etc.) which may improve processing time when the additional images are combined with the long scan 216 to produce a final image that depicts the patient anatomy 212, the first non-linear anomaly 220, and the second nonlinear anomaly 224.

[0108] Once the additional images depicting the first non-linear anomaly 220 and / or the second non-linear anomaly 224 are captured, the processor 104 may use image processing 120 to merge the long scan 216 with the additional images to produce a final long scan image. For example, the processor 104 may generate a panoramic image that comprises the initial long scan and the additional images, such that the patient anatomy and the non-linear anomalies thereof are depicted in a single image. The panoramic image may be generated by the processor 104 using one or more transformation 124 and / or registration 128 to transform the reconstructed images into a panoramic. The processor 104 may use one or more algorithms or data models in generating the panoramic image, such as Random Sample Consensus (RANSAC), Speeded Up Robust Features (SURF), K- nearest neighbors (KNN), Scale Invariant Feature Transformation (SIFT), and the like.

[0109] With reference to Fig. 2E, a lateral view 204 depicting the patient anatomy 212 according to at least one embodiment of the present disclosure is shown. As the long scan 216 is performed, the position of the patient anatomy 212 may be tracked. The patient anatomy 212 may be tracked by the navigation system 118 using one or more cameras and navigation markers disposed proximate the patient anatomy 212 (e.g., optical navigation markers). The one or more cameras may optically capture the navigation markers, and the processor 104 may use image processing 120 and segmentation 122 to respectively process signals from the cameras to produce images andsegment the produced images to identify the navigation markers. Based on the position of the navigation markers (as well as changes thereto), the navigation system 118 may determine the position of the patient anatomy 212 (as well as changes thereto). In some embodiments, the patient anatomy 212 may be localized to one or more localizers (e.g., navigation markers proximate the patient anatomy 212), such that the navigation system 118 can track the position of the patient anatomy 212 during the surgery or surgical procedure.

[0110] The navigation system 118 may also track the imaging device 112 as images are captured during the long scan process. The imaging device 112 may be tracked similarly to the patient anatomy 212 (e.g., using navigation markers). The navigation system 118 may, through a processor 104 using registration 128, determine the position of the imaging device 112 relative to the patient anatomy 212, and vice versa. The navigation system 118 may then navigate the imaging device 112 relative to the patient anatomy 212 during the long scan process. For example, the navigation system 118 may cause the imaging device 112 to move off the axis 206 during the long scan process, such that the imaging device 112 can capture images of the first non-linear anomaly 220 and / or the second non-linear anomaly 224. As depicted in Fig. 2D, the imaging device 112 may capture the first image 208 and the fourth image 236 while moving along the axis 206 during the long scan process, but may be moved off the axis 206 by the navigation system 118 due to the tracking of the patient anatomy 212. In other words, the navigation system 118 may determine based on the tracking of the patient anatomy 212 that the patient anatomy 212 curves away from the axis 206. The navigation system 118 may then move the imaging device 112 along a path that matches the curve, such that the imaging device 112 images the patient anatomy 212. In this example, the fifth image 240 may be generated after the imaging device 112 away from the axis 206, and may depict the first non-linear anomaly 220. The tracking of the patient anatomy 212 and the movement of the imaging device 112 along a path that matches the shape of the patient anatomy 212 may continue until the long scan process is complete.

[0111] In some embodiments, the processor 104 may use transformation 124 to predict the next non-linear anomaly in the patient anatomy 212 during the long scan process, and instruct the navigation system 118 accordingly. For example, the fifth image 240 may be captured by the imaging device 112, and the processor 104 may use segmentation 122 to segment the fifth image 240 into a plurality of segments. The segments may include or depict a non-linear anomaly, as well as portions of the patient anatomy 212. For example, when the first non-linear anomaly 220comprises a transition in the spine from the lumbar curvature to the thoracic curvature, a first segment may depict a lumbar vertebra (e.g., the LI vertebra) and a thoracic vertebra (e.g., T12 vertebra). The navigation system 118 may then predict, based on the movement of the source 138 and the detector 140 relative to the patient 148, the position of the source 138 and the detector 140 relative to the thoracic vertebra at a later time. In some embodiments, the navigation system 118 may then adjust the movement of the source 138 and / or the detector 140 such that the thoracic vertebra is imaged at the later time.

[0112] Additionally or alternatively, the processor 104 may adjust the pose of the collimator 144 to account for the position of the first non-linear anomaly 220. For example, as the source 138 and the detector 140 move relative to the patient 148, the navigation system 118 may track the position of the patient anatomy 212 relative to the source 138 and the detector 140 and adjust the collimator 144 such that anatomical tissues adjacent to the patient anatomy 212 receive less radiation than the patient anatomy 212. As shown in Fig. 2E, a first region 252, a second region 256, and a third region 260 may be exposed to the source 138 and the detector 140 at respective first, second, and third times. The processor 104 may determine, for each of the regions 252, 256, 260, a respective segment 264A-264C that comprises the patient anatomy 212. The processor 104 may then adjust the pose of the collimator 144 such that the segments 264A-264C are respectively imaged at the first, second, and third times, while the surrounding anatomical tissue (represented by the area of the first region 252 not occupied by the first segment 264A, the area of the second region 256 not occupied by the second segment 264B, the area of the third region 260 not occupied by the third segment 264C, etc.) receives less radiation from the source 138. In some embodiments, the processor 104 may cause one or more shutters of the collimator 144 to move relative to the source 138 such that the radiation beam emitted from the source 138 is focused to the segments 264 A- 264C.

[0113] In some embodiments, the processor 104 may predict the second region 256 based on the positioning of the imaging device 112 relative to the first region 252. For example, once the imaging device 112 has imaged the first segment 264A, the processor 104 may process the data generated by the detector 140 using image processing 120 to generate a reconstructed image. The processor 104 may then segment the reconstructed image using segmentation 122, and identify the patient anatomy 212. Then, the processor 104 may predict the location of the second region 256based on the tracking of the imaging device 112, based on the portion of the patient anatomy 212 depicted in the reconstructed image, combinations thereof, and the like.

[0114] While embodiments have been discussed herein thus far with respect to the lateral view 204, the imaging device 112 may additionally or alternatively capture long scans of the patient 148 in alternative views, such as a coronal view 268. The coronal view 268, as depicted in Fig. 2F, may similarly include the long scan 216 and the first and second non-linear anomalies 220, 224. The processor 104 may perform similar functions to those discussed above with respect to the lateral view 204 to generate a final long scan of the coronal view 268 that depicts the patient anatomy 212, the first non-linear anomaly 220, and the second non-linear anomaly 224.

[0115] Fig. 3 depicts a method 300 that may be used, for example, to capture a long scan of a patient that compensates for non-linear anomalies of the patient.

[0116] The method 300 (and / or one or more steps thereof) may be carried out or otherwise performed, for example, by at least one processor. The at least one processor may be the same as or similar to the processor(s) 104 of the computing device 102 described above. The at least one processor may be part of a robot (such as a robot 114) or part of a navigation system (such as a navigation system 118). A processor other than any processor described herein may also be used to execute the method 300. The at least one processor may perform the method 300 by executing elements stored in a memory such as the memory 106. The elements stored in memory and executed by the processor may cause the processor to execute one or more steps of a function as shown in method 300. One or more portions of a method 300 may be performed by the processor executing any of the contents of memory, such as an image processing 120, a segmentation 122, a transformation 124, and / or a registration 128.

[0117] The method 300 comprises initiating a long scan process for a patient anatomy (step 304). The long scan process may include the source 138 and the detector 140 moving relative to the patient 148 (or vice versa), such as when the table 150 holding the patient 148 moves along a direction of the arrow 136 as shown in Fig. IB. The patient anatomy 212 may comprise the spine of the patient 148. Additionally or alternatively, the patient anatomy 212 may comprise any other anatomical feature of the patient 148. In some embodiments, the source 138 and the detector 140 may move relative to the patient 148 at a predetermined and / or fixed rate.

[0118] The method 300 also comprises determining that at least some of the patient anatomy comprises a non-linear anomaly (step 308). The non-linear anomaly may be determined by usingthe processor 104 to process one or more images of the patient anatomy 212. For example, the source 138 and / or the detector 140 may capture images of the patient 148, and the processor 104 may use image processing 120 to generate reconstructed images of the patient 148. The processor 104 may then use segmentation 122 to segment the reconstructed images and identify the patient anatomy 212. Based on the segmenting, the processor 104 may identify portions of the patient anatomy 212 that comprise non-linear anomalies. For example, the patient anatomy 212 may comprise the spine of the patient 148 and processor 104 may determine that the thoracic vertebrae of the spine curve away from a center axis (e.g., axis 206) that runs through the patient 148, constituting a non-linear anomaly.

[0119] The method 300 also comprises implementing a long scan adjustment that compensates for the non-linear anomaly (step 312). The long scan adjustment may comprise causing the source 138 and the detector 140 to move relative to the patient anatomy 212 such that the non-linear anomaly is imaged by the imaging device 112. Continuing the above example, the curvature of the thoracic vertebrae may result in one or more thoracic vertebra (e.g., T9, T8, T7, etc.) being positioned off the axis 206 along which the long scan is performed. The long scan adjustment may compensate for this positioning by causing the source 138 and the detector 140 to move along a path defined by the curve of the spine, such that the thoracic vertebra positioned off the axis 206 are imaged by the imaging device 112.

[0120] Additionally or alternatively, the long scan adjustment may comprise capturing images that depict the non-linear anomaly after the initial long scan process is complete. For example, the long scan may proceed with the source 138 and the detector 140 moving along the axis 206 without causing the source 138 and the detector 140 to move off the axis 206. Once the processor 104 has received the signals from the detector 140 and reconstructed the long scan 216 (e.g., using image processing 120), the processor 104 may use segmentation 122 to segment the long scan 216 and identify one or more non-linear anomalies associated with the patient anatomy 212 that have not been captured. The processor 104 may then instruct the source 138 and the detector 140 to move into a position where the non-linear anomalies can be imaged. In some embodiments, the processor 104 may render information about the segmented long scan 216, information about the missing non-linear anomalies, combinations thereof, and the like to a display such as the user interface 110. For example, the processor 104 may render a depiction of the segmented long scan 216 that includes labels indicating locations of the non-linear anomalies that require additional images tobe captured. In some embodiments, user input may be required before the source 138 and the detector 140 capture the additional images (e.g., the user must provide input via the user interface 110). In other embodiments, the additional images may be automatically captured by the source 138 and the detector 140 after the processor 104 has determined the location of the non-linear anomalies.

[0121] The method 300 also comprises outputting a final long scan image that depicts the patient anatomy including the non-linear anomaly (step 316). The final long scan image may incorporate the long scan adjustment, such that the non-linear anomaly is depicted in the final long scan image. When the long scan adjustment comprises adjusting the position of the source 138 and the detector 140 to image the non-linear anomaly during the long scan, the final long scan image may comprise one or more images of the patient anatomy 212 as well as the non-linear anomaly. When the long scan adjustment comprises capturing additional images after an initial long scan has been completed, the final long scan may be a panoramic image of the images captured during the long scan process and the additional images. The panoramic image may be generated by the processor 104 using one or more transformation 124s and / or registration 128 to transform the reconstructed images into a panoramic. The processor 104 may use one or more algorithms or data models to generate the panoramic image, such as RANSAC, SURF, KNN, SIFT, and the like.

[0122] The present disclosure encompasses embodiments of the method 300 that comprise more or fewer steps than those described above, and / or one or more steps that are different than the steps described above.

[0123] Fig. 4 depicts a method 400 that may be used, for example, to dynamically adjust the path of the source 138 and the detector 140 to capture non-linear anomalies during the long scan process.

[0124] The method 400 (and / or one or more steps thereof) may be carried out or otherwise performed, for example, by at least one processor. The at least one processor may be the same as or similar to the processor(s) 104 of the computing device 102 described above. The at least one processor may be part of a robot (such as a robot 114) or part of a navigation system (such as a navigation system 118). A processor other than any processor described herein may also be used to execute the method 400. The at least one processor may perform the method 400 by executing elements stored in a memory such as the memory 106. The elements stored in memory and executed by the processor may cause the processor to execute one or more steps of a function as shown in method 400. One or more portions of a method 400 may be performed by the processor executingany of the contents of memory, such as an image processing 120, a segmentation 122, a transformation 124, and / or a registration 128.

[0125] The method 400 comprises tracking aposition of patient anatomy (step 404). The tracking may be performed by the navigation system 118 using one or more cameras and navigation markers disposed proximate the patient anatomy 212. The navigation markers may be imaged by the one or more cameras, and image data may be generated that can be processed by the processor 104. The image data may reflect the position and / or changes in position of the navigation markers, such that the navigation system 118 can determine, based on the known pose of the navigation markers relative to the patient anatomy 212, the position and / or changes in position of the patient anatomy 212.

[0126] The method 400 also comprises capturing, at a first time, an image depicting a first portion of the patient anatomy and a non-linear anomaly (step 408). The image may be captured using the imaging device 112, such as when the source 138 and the detector 140 are positioned on either side of the patient anatomy 212 and a radiation beam emitted from the source 138 is received at the detector 140. The signal readout from the detector 140 may be used by the processor 104 using image processing 120 to generate the image. The image may be similar to or the same as the first image 208, which may depict the first portion of the patient anatomy 212 as well as the first nonlinear anomaly 220. The first portion of the patient anatomy 212 may comprise one or more vertebrae that reside along the axis 206. The first non-linear anomaly 220 may result from the natural curvature of the spine, and may comprise one or more vertebrae that do not fall along the axis 206.

[0127] The method 400 also comprises segmenting the image into at least two segments, a first segment including the first portion of the patient anatomy and a second segment including the nonlinear anomaly (step 412). The processor 104 may use segmentation 122 to segment the image into at least two segments, where the first segment comprises the first portion of the patient anatomy, such as a vertebra, and a second segment including the non-linear anomaly, such as a vertebra that does not lie along the axis 206. In some embodiments, the processor 104 may render the segmented image to a display (e.g., user interface 110). The processor 104 may also segment the image into additional segments, such as when the patient anatomy 212 comprise multiple non-linear anomalies. For example, when the image depicts a plurality of vertebrae, the processor 104 may segment each of the vertebrae with a separate segment. 1

[0128] The method 400 also comprises predicting, based on the segmenting, a position of the non-linear anomaly relative to the image capture device at a second time (step 416). The image capture device may be or comprise the source 138 and the detector 140, or more generally the imaging device 112. Once the image is segmented, the processor 104 may identify the non-linear anomaly and determine, based on the position of the non-linear anomaly in the image, the position of the imaging device 112 relative to the non-linear anomaly at a time when the image was captured. The processor 104 may then use information about when the image was captured, information about the position of the patient anatomy 212 (e.g., based on information from the navigation system 118), information about the movement speed of the source 138 and the detector 140 relative to the patient 148 during the long scan process, combinations thereof, and the like in predicting the position of the non-linear anomaly relative to the source 138 and / or the detector 140 at the second later time. For example, the processor 104 may determine the movement speed of the source 138 and the detector 140 and the determined position of the imaging device 112 relative to the non-linear anomaly at the time when the image was captured to predict the position of the nonlinear anomaly relative to the image capture device at the second time.

[0129] The method 400 also comprises changing, based on the predicted position of the nonlinear anomaly at the second time, an orientation of an imaging collimator (step 420). The imaging collimator, such as the collimator 144, may be changed such that the non-linear anomaly will be exposed to the radiation emitted by the source 138, while surrounding anatomical tissue is exposed to reduced radiation due to the collimator 144. In some cases, the collimator 144 may comprise one or more degrees of freedom (e.g., one, two, or three degrees of freedom) with one or more shutters capable of being opened or closed to manipulate the shape and / or direction of the radiation beam emitted from the source 138. The processor 104 may actuate one or more motors connected to the shutters to adjust the orientation of the collimator 144. For example, when the non-linear anomaly comprises a vertebra in the second region 256, the orientation of the collimator 144 may be changed such that the area depicted by the second segment 264B (including the vertebra) receives the radiation beam, while the remainder of the second region 256 not included in the second segment 264B (e.g., adipose tissue surrounding the vertebra) may experience reduced radiation.

[0130] The method 400 also comprises capturing, at a second time, a second image depicting the non-linear anomaly (step 424). Once the collimator 144 has been adjusted and the source 138 and the detector 140 have moved relative to the non-linear anomaly, the source 138 may emit radiationthat passes through the non-linear anomaly and is then detected by the detector 140. Due to the positioning of the collimator 144, the non-linear anomaly may be captured in the resulting image generated by the processor 104, while the nearby tissue may experience reduced radiation.

[0131] The present disclosure encompasses embodiments of the method 400 that comprise more or fewer steps than those described above, and / or one or more steps that are different than the steps described above.

[0132] Fig. 5 depicts a method 500 that may be used, for example, to adjust an initial long scan image with additional image views to account for non-linear anomalies in patient anatomy.

[0133] The method 500 (and / or one or more steps thereof) may be carried out or otherwise performed, for example, by at least one processor. The at least one processor may be the same as or similar to the processor(s) 104 of the computing device 102 described above. The at least one processor may be part of a robot (such as a robot 114) or part of a navigation system (such as a navigation system 118). A processor other than any processor described herein may also be used to execute the method 500. The at least one processor may perform the method 500 by executing elements stored in a memory such as the memory 106. The elements stored in the memory and executed by the processor may cause the processor to execute one or more steps of a function as shown in method 500. One or more portions of a method 500 may be performed by the processor executing any of the contents of memory, such as an image processing 120, a segmentation 122, a transformation 124, and / or a registration 128.

[0134] The method 500 comprises detecting an initial long scan image of patient anatomy failed to capture a non-linear anomaly (step 504). The initial long scan may be or comprise the long scan 216. The initial long scan image may not capture, for example, the first non-linear anomaly 220 and / or the second non-linear anomaly 224 due to the position of the first non-linear anomaly 220 and / or the second non-linear anomaly 224 relative to the imaging device 112 when the imaging device 112 captures the initial long scan image. The processor 104 may segment the initial long scan using segmentation 122, and may identify one or more portions of the patient anatomy 212 (e.g., first non-linear anomaly 220, the second non-linear anomaly 224, etc.) that were not captured by the initial long scan. In some embodiments, the processor 104 may render such information to the user interface 110.

[0135] The method 500 also comprises causing an image capture device to move into a position to capture at least one additional image (step 508). The processor 104 may cause the imaging device112 to move such that the source 138 and the detector 140 are positioned on either side of the nonlinear anomaly, such that the radiation beam emitted by the source 138 passes through the nonlinear anomaly before being received at the detector 140. In some embodiments, the system 100 may require user input (e.g., via the user interface 110) before the image capture device moves into position to capture the additional image(s). For example, the user may determine that the additional images are unnecessary, such as when the user determines that the additional radiation exposure is not warranted, that the additional images will provide superfluous information, and / or for any other reason. In other embodiments, the imaging device 112 may automatically move into place to capture the additional image without user input.

[0136] The method 500 also comprises capturing the at least one additional image of the patient anatomy, wherein the at least one additional image includes the non-linear anomaly (step 512). The additional image(s) of the non-linear anomalies may be captured by the source 138 and the detector 140 and generated by the processor 104 using image processing 120. In some embodiments, a plurality of additional images may be captured that depict the non-linear anomaly from various angles. In some embodiments, capturing of the additional image(s) may incorporate one or more changes to the collimator 144 as discussed above, such that the additional images depict the nonlinear anomaly while reducing the exposure of surrounding tissue to radiation.

[0137] The method 500 also comprises merging the at least one additional image with the initial long scan image to produce a final long scan image that depicts the patient anatomy including the non-linear anomaly (step 516). The merging may comprise generating a panoramic image of the initial long scan and the additional images, such that the patient anatomy and the non-linear anomalies thereof are depicted in a single image. The panoramic image may be generated by the processor 104 using one or more transformation 124 and / or registration 128 to transform the reconstructed images into a panoramic. The processor 104 may generate the panoramic image using use one or more algorithms or data models, such as RANSAC, SURF, KNN, SIFT, and the like.

[0138] The present disclosure encompasses embodiments of the method 500 that comprise more or fewer steps than those described above, and / or one or more steps that are different than the steps described above.

[0139] As noted above, the present disclosure encompasses methods with fewer than all of the steps identified in Figs. 3, 4, and 5 (and the corresponding description of the methods 300, 400, and 500), as well as methods that include additional steps beyond those identified in Figs. 3, 4, and5 (and the corresponding description of the methods 300, 400, and 500). The present disclosure also encompasses methods that comprise one or more steps from one method described herein, and one or more steps from another method described herein. Any correlation described herein may be or comprise a registration or any other correlation.

[0140] The foregoing is not intended to limit the disclosure to the form or forms disclosed herein. In the foregoing Detailed Description, for example, various features of the disclosure are grouped together in one or more aspects, embodiments, and / or configurations for the purpose of streamlining the disclosure. The features of the aspects, embodiments, and / or configurations of the disclosure may be combined in alternate aspects, embodiments, and / or configurations other than those discussed above. This method of disclosure is not to be interpreted as reflecting an intention that the claims require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed aspect, embodiment, and / or configuration. Thus, the following claims are hereby incorporated into this Detailed Description, with each claim standing on its own as a separate preferred embodiment of the disclosure.

[0141] Moreover, though the foregoing has included description of one or more aspects, embodiments, and / or configurations and certain variations and modifications, other variations, combinations, and modifications are within the scope of the disclosure, e.g., as may be within the skill and knowledge of those in the art, after understanding the present disclosure. It is intended to obtain rights which include alternative aspects, embodiments, and / or configurations to the extent permitted, including alternate, interchangeable and / or equivalent structures, functions, ranges or steps to those claimed, whether or not such alternate, interchangeable and / or equivalent structures, functions, ranges or steps are disclosed herein, and without intending to publicly dedicate any patentable subject matter.

[0142] Example 1. An imaging system, comprising: an image capture device; a processor coupled with the image capture device; and memory coupled with the processor and storing data thereon that, when executed by the processor, enable the processor to: initiate a long scan process for a patient anatomy using the image capture device; determine that at least some of the patient anatomy comprises a non-linear anomaly;implement a long scan adjustment that compensates for the non-linear anomaly; and output a final long scan image that depicts the patient anatomy including the non-linear anomaly.

[0143] Example 2. The imaging system of example 1, wherein the long scan adjustment comprises dynamically adjusting a path of the image capture device to capture the non-linear anomaly during the long scan process.

[0144] Example 3. The imaging system of example 2, wherein the dynamically adjusting comprises: tracking a position of the patient anatomy; and adjusting, based on the tracking, a pose of the image capture device relative to the patient anatomy.

[0145] Example 4. The imaging system of example 3, wherein the tracking the position of the patient anatomy comprises: capturing, at a first time, an image depicting a first portion of the patient anatomy and the non-linear anomaly; segmenting the image into at least two segments, a first segment including the first portion of the patient anatomy and a second segment including the non-linear anomaly; and predicting, based on the segmenting, a position of the non-linear anomaly relative to the image capture device at a second time.

[0146] Example 5. The imaging system of example 4, wherein the image capture device comprises a radiation source and an imaging collimator disposed at least partially over the radiation source, and wherein the adjusting the pose of the image capture device comprises: changing, based on the predicted position of the non-linear anomaly at the second time, an orientation of the imaging collimator.

[0147] Example 6. The imaging system of example 5, further comprising: capturing, at the second time, a second image depicting the non-linear anomaly.

[0148] Example 7. The imaging system of example 1, wherein the long scan adjustment comprises: detecting an initial long scan image of the patient anatomy failed to capture the non-linear anomaly; capturing at least one additional image of the patient anatomy, wherein the at least one additional image includes the non-linear anomaly; and merging the at least one additional image with the initial long scan image to produce the final long scan image that depicts the patient anatomy including the non-linear anomaly.

[0149] Example 8. The imaging system of example 7, wherein the non-linear anomaly comprises a curvature of the patient anatomy.

[0150] Example 9. The imaging system of example 7, wherein the non-linear anomaly comprises an anatomical element different from the patient anatomy.

[0151] Example 10. The imaging system of example 9, wherein the merging further comprises:

[0152] generating a panoramic image depicting the patient anatomy and the non-linear anomaly.

[0153] Example 11. The imaging system of example 7, wherein the capturing the at least one additional image of the patient anatomy comprises: causing the image capture device to move into a position to capture the at least one additional image.

[0154] Example 12. The imaging system of example 1, wherein the image capture device comprises at least one of an 0-arm and a C-arm.

[0155] Example 13. The imaging system of example 1, wherein the final long scan image comprises a fluoroscopic image, and wherein the fluoroscopic image is rendered to a display.

[0156] Example 14. A system, comprising:a processor; and a memory storing data thereon that, when processed by the processor, enable the processor to: initiate a long scan process for a patient anatomy using an image capture device; determine that at least some of the patient anatomy comprises a non-linear anomaly; implement a long scan adjustment that compensates for the non-linear anomaly; and output a final long scan image that depicts the patient anatomy including the non-linear anomaly.

[0157] Example 15. The system of example 14, wherein the long scan adjustment comprises dynamically adjusting a path of the image capture device to capture the non-linear anomaly during the long scan process.

[0158] Example 16. The system of example 15, wherein the dynamically adjusting comprises: tracking a position of the patient anatomy; and adjusting, based on the tracking, a pose of the image capture device relative to the patient anatomy.

[0159] Example 17. The system of example 16, wherein the tracking the position of the patient anatomy comprises: capturing, at a first time, an image depicting a first portion of the patient anatomy and the non-linear anomaly; segmenting the image into at least two segments, a first segment including the first portion of the patient anatomy and a second segment including the non-linear anomaly; and predicting, based on the segmenting, a position of the non-linear anomaly relative to the image capture device at a second time.

[0160] Example 18. The system of example 17, wherein the image capture device comprises a radiation source and an imaging collimator disposed at least partially over the radiation source, and wherein the adjusting the pose of the image capture device comprises:changing, based on the predicted position of the non-linear anomaly at the second time, an orientation of the imaging collimator.

[0161] Example 19. The system of example 18, further comprising: capturing, at the second time, a second image depicting the non-linear anomaly.

[0162] Example 20. The system of example 14, wherein the long scan adjustment comprises: detecting an initial long scan image of the patient anatomy failed to capture the non-linear anomaly; capturing at least one additional image of the patient anatomy, wherein the at least one additional image includes the non-linear anomaly; and merging the at least one additional image with the initial long scan image to produce the final long scan image that depicts the patient anatomy including the non-linear anomaly.

[0163] Example 21. The system of example 20, wherein the non-linear anomaly comprises a curvature of the patient anatomy.

[0164] Example 22. The system of example 20, wherein the non-linear anomaly comprises an anatomical element different from the patient anatomy.

[0165] Example 23. The system of example 22, wherein the merging further comprises: generating a panoramic image depicting the patient anatomy and the non-linear anomaly.

[0166] Example 24. The system of claim 20, wherein the capturing the at least one additional image of the patient anatomy comprises: causing the image capture device to move into a position to capture the at least one additional image.

[0167] Example 25. The system of example 14, wherein the final long scan image comprises a fluoroscopic image, and wherein the fluoroscopic image is rendered to a display.

[0168] Example 26. A method, comprising: initiating a long scan process for a patient anatomy; determining that at least some of the patient anatomy comprises a non-linear anomaly; implementing a long scan adjustment that compensates for the non-linear anomaly; and outputting a final long scan image that depicts the patient anatomy including the nonlinear anomaly.

[0169] Example 27. The method of example 26, further comprising: dynamically adjusting a path of an image capture device to capture the non-linear anomaly during the long scan process.

[0170] Example 28. The method of example 27, further comprising: tracking a position of the patient anatomy; and

[0171] adjusting, based on the tracking, a pose of the image capture device relative to the patient anatomy.

[0172] Example 29. The method of example 28, further comprising: capturing, at a first time, an image depicting a first portion of the patient anatomy and the non-linear anomaly; segmenting the image into at least two segments, a first segment including the first portion of the patient anatomy and a second segment including the non-linear anomaly; and predicting, based on the segmenting, a position of the non-linear anomaly relative to the image capture device at a second time.

[0173] Example 30. The method of example 29, further comprising: changing, based on the predicted position of the non-linear anomaly at the second time, an orientation of an imaging collimator.

[0174] Example 31. The method of example 30, further comprising: capturing, at the second time, a second image depicting the non-linear anomaly.

[0175] Example 32. The method of example 26, further comprising: detecting an initial long scan image of the patient anatomy failed to capture the non-linear anomaly; capturing at least one additional image of the patient anatomy, wherein the at least one additional image includes the non-linear anomaly; and merging the at least one additional image with the initial long scan image to produce the final long scan image that depicts the patient anatomy including the non-linear anomaly.

[0176] Example 33. The method of example 32, wherein the non-linear anomaly comprises a curvature of the patient anatomy.

[0177] Example 34. The method of example 32, wherein the non-linear anomaly comprises an anatomical element different from the patient anatomy.

[0178] Example 35. The method of claim 34, further comprising: generating a panoramic image depicting the patient anatomy and the non-linear anomaly.

[0179] Example 36. The method of example 32, further comprising: causing an image capture device to move into a position to capture the at least one additional image.

[0180] Example 37. The method of example 26, further comprising: rendering the final long scan image to a display.

[0181] Example 38. An imaging system (100), comprising: an image capture device (112); a processor (104) coupled with the image capture device (112); and memory (106) coupled with the processor (104) and storing data thereon that, when executed by the processor (104), enable the processor (104) to: initiate a long scan process for a patient anatomy (212) using the image capture device(112);determine that at least some of the patient anatomy (212) comprises a non-linear anomaly (220, 224); implement a long scan adjustment that compensates for the non-linear anomaly (220, 224); and output a final long scan image that depicts the patient anatomy (212) including the nonlinear anomaly (220, 224).

[0182] Example 39. The imaging system according to example 38, wherein the long scan adjustment comprises dynamically adjusting a path of the image capture device (112) to capture the non-linear anomaly (220, 224) during the long scan process.

[0183] Example 40. The imaging system according to example 39, wherein the dynamically adjusting comprises: tracking a position of the patient anatomy (212); and adjusting, based on the tracking, a pose of the image capture device (112) relative to the patient anatomy (212).

[0184] Example 41. The imaging system according to example 40, wherein the tracking the position of the patient anatomy (212) comprises: capturing, at a first time, an image (208) depicting a first portion of the patient anatomy (212) and the non-linear anomaly (220, 224); segmenting the image (208) into at least two segments (264A-264C), a first segment (264 A) including the first portion of the patient anatomy (212) and a second segment (264B) including the non-linear anomaly (220, 224); and predicting, based on the segmenting, a position of the non-linear anomaly (220, 224) relative to the image capture device (112) at a second time.

[0185] Example 42. The imaging system according to example 40 or 41, wherein the image capture device (112) comprises a radiation source (138) and an imaging collimator (144) disposed at least partially over the radiation source (138), and wherein the adjusting the pose of the image capture device (112) comprises:changing, based on the predicted position of the non-linear anomaly (220, 224) at the second time, an orientation of the imaging collimator (144).

[0186] Example 43. The imaging system according to example 41 or 42, further comprising: capturing, at the second time, a second image (228) depicting the non-linear anomaly (220, 224).

[0187] Example 44. The imaging system according to any of example 38 to 43, wherein the long scan adjustment comprises: detecting an initial long scan image of the patient anatomy (212) failed to capture the nonlinear anomaly (220, 224); capturing at least one additional image (236, 240, 244, 248) of the patient anatomy (212), wherein the at least one additional image (236, 240, 244, 248) includes the non-linear anomaly (220, 224); and merging the at least one additional image (236, 240, 244, 248) with the initial long scan image to produce the final long scan image that depicts the patient anatomy (212) including the non-linear anomaly (220, 224).

[0188] Example 45. The imaging system according to any of examples 38 to 44, wherein the non-linear anomaly (220, 224) comprises a curvature of the patient anatomy (212).

[0189] Example 46. The imaging system according to any of examples 38 to 45, wherein the non-linear anomaly (220, 224) comprises an anatomical element different from the patient anatomy (212).

[0190] Example 47. The imaging system according to any of examples 44 to 46, wherein the merging further comprises:

[0191] generating a panoramic image depicting the patient anatomy (212) and the non-linear anomaly (220, 224).

[0192] Example 48. The imaging system according to any of examples 44 to 47, wherein the capturing the at least one additional image (236, 240, 244, 248) of the patient anatomy (212) comprises: causing the image capture device (112) to move into a position to capture the at least one additional image (236, 240, 244, 248).

[0193] Example 49. The imaging system according to any of examples 38 to 48, wherein the image capture device (112) comprises at least one of an 0-arm and a C-arm.

[0194] Example 50. The imaging system according to any of examples 38 to 49, wherein the final long scan image comprises a fluoroscopic image, and wherein the fluoroscopic image is rendered to a display (110).

[0195] Example 51. A system (100), comprising: a processor (104); and a memory (106) storing data thereon that, when processed by the processor (104), enable the processor (104) to: initiate a long scan process for a patient anatomy (212) using an image capture device (112); determine that at least some of the patient anatomy (212) comprises a non-linear anomaly (220, 224); implement a long scan adjustment that compensates for the non-linear anomaly (220, 224); and output a final long scan image that depicts the patient anatomy (212) including the nonlinear anomaly (220, 224).

[0196] Example 52. A method, comprising: initiating a long scan process for a patient anatomy (212); determining that at least some of the patient anatomy (212) comprises a non-linear anomaly (220, 224);implementing a long scan adjustment that compensates for the non-linear anomaly (220, 224); and outputting a final long scan image that depicts the patient anatomy (212) including the non-linear anomaly (220, 224).

Claims

CLAIMSWHAT IS CLAIMED IS:

1. An imaging system (100), comprising: an image capture device (112); a processor (104) coupled with the image capture device (112); and memory (106) coupled with the processor (104) and storing data thereon that, when executed by the processor (104), enable the processor (104) to: initiate a long scan process for a patient anatomy (212) using the image capture device (112); determine that at least some of the patient anatomy (212) comprises a non-linear anomaly (220, 224); implement a long scan adjustment that compensates for the non-linear anomaly (220, 224); and output a final long scan image that depicts the patient anatomy (212) including the non-linear anomaly (220, 224).

2. The imaging system according to claim 1, wherein the long scan adjustment comprises dynamically adjusting a path of the image capture device (112) to capture the non-linear anomaly (220, 224) during the long scan process.

3. The imaging system according to claim 2, wherein the dynamically adjusting comprises: tracking a position of the patient anatomy (212); and adjusting, based on the tracking, a pose of the image capture device (112) relative to the patient anatomy (212).

4. The imaging system according to claim 3, wherein the tracking the position of the patient anatomy (212) comprises:capturing, at a first time, an image (208) depicting a first portion of the patient anatomy (212) and the non-linear anomaly (220, 224); segmenting the image (208) into at least two segments (264A-264C), a first segment (264A) including the first portion of the patient anatomy (212) and a second segment (264B) including the non-linear anomaly (220, 224); and predicting, based on the segmenting, a position of the non-linear anomaly (220, 224) relative to the image capture device (112) at a second time.

5. The imaging system according to claims 3 or 4, wherein the image capture device (112) comprises a radiation source (138) and an imaging collimator (144) disposed at least partially over the radiation source (138), and wherein the adjusting the pose of the image capture device (112) comprises: changing, based on the predicted position of the non-linear anomaly (220, 224) at the second time, an orientation of the imaging collimator (144).

6. The imaging system according to claims 4 or 5, further comprising: capturing, at the second time, a second image (228) depicting the non-linear anomaly (220, 224).

7. The imaging system according to any of claims 1 to 6, wherein the long scan adjustment comprises: detecting an initial long scan image of the patient anatomy (212) failed to capture the nonlinear anomaly (220, 224); capturing at least one additional image (236, 240, 244, 248) of the patient anatomy (212), wherein the at least one additional image (236, 240, 244, 248) includes the non-linear anomaly (220, 224); and merging the at least one additional image (236, 240, 244, 248) with the initial long scan image to produce the final long scan image that depicts the patient anatomy (212) including the non-linear anomaly (220, 224).

8. The imaging system according to any of claims 1 to 7, wherein the non-linear anomaly (220, 224) comprises a curvature of the patient anatomy (212).

9. The imaging system according to any of claims 1 to 8, wherein the non-linear anomaly (220, 224) comprises an anatomical element different from the patient anatomy (212).

10. The imaging system according to any of claims 7 to 9, wherein the merging further comprises: generating a panoramic image depicting the patient anatomy (212) and the non-linear anomaly (220, 224).

11. The imaging system according to any of claims 7 to 10, wherein the capturing the at least one additional image (236, 240, 244, 248) of the patient anatomy (212) comprises: causing the image capture device (112) to move into a position to capture the at least one additional image (236, 240, 244, 248).

12. The imaging system according to any of claims 1 to 11, wherein the image capture device (112) comprises at least one of an 0-arm and a C-arm.

13. The imaging system according to any of claims 1 to 12, wherein the final long scan image comprises a fluoroscopic image, and wherein the fluoroscopic image is rendered to a display (HO).

14. A system (100), comprising: a processor (104); and a memory (106) storing data thereon that, when processed by the processor (104), enable the processor (104) to: initiate a long scan process for a patient anatomy (212) using an image capture device (112); determine that at least some of the patient anatomy (212) comprises a non-linear anomaly (220, 224);implement a long scan adjustment that compensates for the non-linear anomaly (220, 224); and output a final long scan image that depicts the patient anatomy (212) including the non-linear anomaly (220, 224).

15. A method, comprising: initiating a long scan process for a patient anatomy (212); determining that at least some of the patient anatomy (212) comprises a non-linear anomaly (220, 224); implementing a long scan adjustment that compensates for the non-linear anomaly (220, 224); and outputting a final long scan image that depicts the patient anatomy (212) including the non-linear anomaly (220, 224).

Images