Keyframe Identification for Intravascular Ultrasound Based on Plaque Burden

Abstract

The present disclosure provides for processing a plurality of intravascular ultrasound (IVUS) images to identify key frames, such as proximal key frames, distal key frames, and minimum key frames, from the plurality of IVUS images based on raw lumen area, vessel area, and plaque burden, where some of the plurality of key frames may be re-identified based on manipulation of some other of the plurality of key frames.

Description

[Technical Field]

[0001] The present disclosure relates generally to intravascular ultrasound (IVUS) imaging systems. The present disclosure particularly, but not exclusively, to identifying keyframe markers using plaque burden displayed in IVUS images. This application claims the benefit of U.S. Provisional Patent Application No. 63 / 406,361, filed September 14, 2022, the disclosure of which is incorporated herein by reference. [Background technology]

[0002] Patient-insertable ultrasound devices have proven diagnostic capabilities for a variety of diseases and disorders. For example, intravascular ultrasound (IVUS) imaging systems are used as an imaging modality to diagnose blocked blood vessels and provide information to assist physicians in selecting and placing stents and other devices to restore or increase blood flow.

[0003] An IVUS imaging system includes a control module (having a pulse generator, image acquisition and processing components, and a monitor), a catheter, and a transducer disposed within the catheter. The catheter containing the transducer is positioned within a lumen or cavity in or adjacent to a region to be imaged, such as a blood vessel wall or patient tissue adjacent to a blood vessel wall. The pulse generator within the control module generates electrical pulses that are delivered to the transducer and converted into acoustic pulses that are transmitted through the patient tissue. The patient tissue (or other structure) reflects the acoustic pulses, and the reflected pulses are absorbed by the transducer and converted into electrical pulses. The converted electrical pulses are delivered to the image acquisition and processing components and converted into an image that can be displayed on a monitor.

[0004] However, it can be difficult for physicians to visualize the complete structure of a patient's lumen (e.g., blood vessel) from raw IVUS images. For example, it can be difficult to determine the overall plaque burden, the appropriate size (e.g., diameter and / or length) of a stent to use in correcting any stenosis in the lumen, and where to seat the stent. Therefore, there is a need for systems and methods for processing, annotating, visualizing, and / or displaying images of a patient's lumen based on IVUS images. Summary of the Invention

[0005] This Summary is provided to introduce a selection of concepts in a simplified form that are further described in the Detailed Description. This Summary is not intended to necessarily identify key features or essential features of the claimed subject matter, nor is it intended to aid in determining the scope of the claimed subject matter.

[0006] Generally, the present disclosure provides for processing raw IVUS images to automatically detect lumen and vessel boundaries and identify regions of interest, more specifically, start and end points that encompass frames of interest within a series of IVUS images.

[0007] In some implementations, the present disclosure is embodied as a method, for example, a method for an intravascular ultrasound (IVUS) imaging system. The method includes receiving a series of intravascular ultrasound (IVUS) images of a patient's blood vessel, the series including a proximal IVUS frame, a distal IVUS frame, and a plurality of internal IVUS frames; determining a raw lumen area represented in each of the plurality of internal IVUS frames; determining a smooth lumen area for each of the plurality of internal IVUS frames based on a sampling filter and the raw lumen area; identifying one of the plurality of internal IVUS frames having a smooth lumen area less than or equal to a minimum smooth lumen area among the plurality of internal IVUS frames as a smooth lumen frame; selecting a subset of the plurality of internal IVUS frames including the smooth lumen frame and at least one other internal IVUS frame of the plurality of internal IVUS frames that is collinear with the smooth lumen frame; and identifying one internal IVUS frame of the subset of the plurality of internal IVUS frames having a raw lumen area less than or equal to the lumen area as a minimum key frame.

[0008] Alternatively or additionally in any embodiment of the above method, the subset of the plurality of internal IVUS frames comprises 21 frames. Alternatively or additionally in any embodiment of the above method, the subset of the plurality of internal IVUS frames includes those of the series of IVUS images that represent a distance along the vessel.

[0009] Alternatively or additionally in any embodiment of the above method, the distance is 2 millimeters or less. Alternatively or additionally in any embodiment of the above method, the plurality of internal IVUS frames are positioned between the proximal IVUS frame and the distal IVUS frame.

[0010] Alternatively or additionally, in any embodiment of the above method, the series of IVUS images includes a plurality of IVUS image frames, and the method may comprise designating a first frame in the series of IVUS images as a distal keyframe and designating a last frame in the series of IVUS images as a proximal keyframe.

[0011] Alternatively or additionally in any of the above method embodiments, the method may comprise receiving an indication of the proximal IVUS frame and the distal IVUS frame from an input device.

[0012] Alternatively or additionally, in any embodiment of the above method, the series of IVUS images includes a plurality of IVUS image frames, and identifying one of the plurality of internal IVUS frames having a smooth lumen area less than or equal to a minimum smooth lumen area as a smooth lumen frame may include designating each IVUS image of the plurality of IVUS images disposed between the proximal IVUS frame and the distal IVUS frame as an internal IVUS frame, identifying the minimum smooth lumen area among the plurality of internal IVUS frames, identifying one or more internal IVUS frames having a smooth lumen area equal to the minimum smooth lumen area, and designating an internal IVUS frame of the identified one or more internal IVUS frames that is centered relative to the proximal IVUS frame and the distal IVUS frame as a minimum smooth lumen frame.

[0013] Alternatively or additionally, in any embodiment of the method described above, the sampling filter includes a first sampling filter, and the method may include determining a smoothed lumen area for each of the plurality of IVUS images based on a second sampling filter different from the first sampling filter and the smoothed lumen area.

[0014] Alternatively or additionally, in any of the above method embodiments, the series of IVUS images includes a plurality of IVUS image frames, and the method may comprise identifying an initial proximal search frame and an initial distal search frame, identifying an IVUS image frame having the smallest smooth lumen area from among the plurality of IVUS image frames located between the initial proximal search frame and the initial distal search frame, identifying one of the plurality of IVUS image frames located within a first distance from the IVUS image frame and having the smallest raw lumen area as a central search frame, identifying one of the plurality of IVUS image frames located within a second distance distal to the central search frame and having smooth plaque loads and raw plaque loads less than thresholds as a distal key frame, and identifying one of the plurality of IVUS image frames located within the second distance proximal to the central search frame and having smooth plaque loads and raw plaque loads less than the thresholds as a proximal key frame.

[0015] Alternatively or additionally, in any embodiment of the above method, the threshold value is between 40 percent and 60 percent. Alternatively or additionally, in any embodiment of the above method, the second distance is 5 millimeters or less.

[0016] Alternatively or additionally, in any embodiment of the above method, the first distance is 1 millimeter or less. In some implementations, the present disclosure may be embodied as an apparatus including a processor of an intravascular ultrasound (IVUS) imaging system coupled to a memory, the memory including instructions executable by the processor, the processor configured to execute the instructions, which when executed cause the processor to perform a method of any combination of the above-described embodiments.

[0017] In some implementations, the present disclosure may be embodied as at least one machine-readable storage device comprising a plurality of instructions that, when executed by a processor of an intravascular ultrasound (IVUS) imaging system, cause the processor to perform the method of any combination of the above-described embodiments.

[0018] In some implementations, the present disclosure may be embodied as an apparatus for an intravascular ultrasound (IVUS) imaging system comprising: a circuit for coupling to the IVUS system; a memory device for storing a plurality of instructions; and a processor coupled to the circuit and the memory device. The processor is configured to execute the instructions, which, when executed, cause the computing device to: receive a series of intravascular ultrasound (IVUS) images of a patient's blood vessel, the series including a proximal IVUS frame, a distal IVUS frame, and a plurality of internal IVUS frames; determine a raw lumen area represented in each of the plurality of internal IVUS frames; determine a smooth lumen area for each of the plurality of internal IVUS frames based on a sampling filter and the raw lumen area; identify one of the plurality of internal IVUS frames having a smooth lumen area less than or equal to a minimum smooth lumen area as a smooth lumen frame; select a subset of the plurality of internal IVUS frames including the smooth lumen frame and at least one other internal IVUS frame of the plurality of internal IVUS frames that is collinear with the smooth lumen frame; and identify one internal IVUS frame of the subset of the plurality of internal IVUS frames having a raw lumen area less than or equal to the lumen area as a minimum key frame.

[0019] Alternatively or additionally in any embodiment of the above apparatus, the subset of the plurality of internal IVUS frames comprises 21 frames. Alternatively or additionally in any of the above apparatus embodiments, the subset of the plurality of internal IVUS frames includes those of the series of IVUS images that represent a distance along the vessel.

[0020] Alternatively or additionally in any embodiment of the above device, the distance is 2 millimeters or less. Alternatively or additionally, in any of the above device embodiments, the plurality of internal IVUS frames are disposed between the proximal IVUS frame and the distal IVUS frame.

[0021] Alternatively or additionally, in any of the above device embodiments, the series of IVUS images includes a plurality of IVUS image frames, and the memory device may further include a plurality of instructions that, when executed by the processor, cause the IVUS imaging system to designate a first frame in the series of IVUS images as a distal keyframe and a last frame in the series of IVUS images as a proximal keyframe.

[0022] Alternatively or additionally, in any of the embodiments of the above device, the memory device may further include a plurality of instructions that, when executed by the processor, cause the IVUS imaging system to receive an indication of the proximal IVUS frame and the distal IVUS frame from an input device.

[0023] Alternatively or additionally in any of the above device embodiments, the series of IVUS images includes a plurality of IVUS image frames, and identifying one of the plurality of internal IVUS frames having a smooth lumen area less than or equal to the minimum smooth lumen area as a smooth lumen frame includes designating each IVUS image of the plurality of IVUS images that is positioned between the proximal IVUS frame and the distal IVUS frame as an internal IVUS frame, identifying the minimum smooth lumen area among the plurality of internal IVUS frames, identifying one or more internal IVUS frames that have a smooth lumen area equal to the minimum smooth lumen area, and designating an internal IVUS frame of the identified one or more internal IVUS frames that is centered relative to the proximal IVUS frame and the distal IVUS frame as the minimum smooth lumen frame.

[0024] Alternatively or additionally, in any of the above device embodiments, the sampling filter includes a first sampling filter, and the instructions, when executed, cause the computing device to determine a smoothed lumen area for each of the plurality of IVUS images based on a second sampling filter different from the first sampling filter and the smoothed lumen area.

[0025] Alternatively or additionally, in any of the above device embodiments, the series of IVUS images includes a plurality of IVUS image frames, and the memory device may further include a plurality of instructions, when executed by the processor, that cause the IVUS imaging system to: identify an initial proximal search frame and an initial distal search frame; identify an IVUS image frame having the smallest smooth lumen area from among the plurality of IVUS image frames that are located between the initial proximal search frame and the initial distal search frame; identify one of the plurality of IVUS image frames that is located within a first distance from the IVUS image frame and has the smallest raw lumen area as a central search frame; identify one of the plurality of IVUS image frames that is located within a second distance distal to the central search frame and has smooth plaque load and raw plaque load less than thresholds as a distal key frame; and identify one of the plurality of IVUS image frames that is located within the second distance proximal to the central search frame and has smooth plaque load and raw plaque load less than the thresholds as a proximal key frame.

[0026] Alternatively or additionally in any embodiment of the above apparatus, the threshold value is between 40 percent and 60 percent. Alternatively or additionally, in any embodiment of the above apparatus, the first distance is 1 millimeter (mm) or less and the second distance is 5 mm or less.

[0027] In some implementations, the present disclosure may be embodied as at least one machine-readable storage device that, in response to being executed by a processor of an intravascular ultrasound (IVUS) imaging system, causes the processor to: receive a series of intravascular ultrasound (IVUS) images of a patient's blood vessel, the series including a proximal IVUS frame, a distal IVUS frame, and a plurality of internal IVUS frames; determine a raw lumen area represented in each of the plurality of internal IVUS frames; for each of the plurality of internal IVUS frames, determine a smoothed lumen area based on a sampling filter and the raw lumen area; The method includes a plurality of instructions to execute the steps of: identifying one of the plurality of internal IVUS frames having a smooth lumen area less than or equal to a smooth lumen area as a smooth lumen frame; selecting a subset of the plurality of internal IVUS frames including the smooth lumen frame and at least one other internal IVUS frame of the plurality of internal IVUS frames that is collinear with the smooth lumen frame; and identifying one internal IVUS frame of the subset of the plurality of internal IVUS frames having a smooth lumen area less than or equal to the lumen area as a minimum key frame among the subset of the plurality of internal IVUS frames.

[0028] Alternatively or additionally in any embodiment of the at least one machine-readable storage device described above, the subset of the plurality of internal IVUS frames comprises 21 frames. Alternatively or additionally in any embodiment of the at least one machine-readable storage device described above, the subset of the plurality of internal IVUS frames includes those of the series of IVUS images that represent a distance along the blood vessel.

[0029] Alternatively or additionally, in any embodiment of the at least one machine-readable storage device described above, the distance is less than or equal to 2 millimeters. Alternatively or additionally in any embodiment of the at least one machine-readable storage device described above, the plurality of internal IVUS frames are disposed between the proximal IVUS frame and the distal IVUS frame.

[0030] Alternatively or additionally, in any embodiment of the at least one machine-readable storage device, the series of IVUS images includes a plurality of IVUS image frames, and the instructions, in response to being executed by the processor, may cause the processor to designate a first frame in the series of IVUS images as a distal key frame and to designate a last frame in the series of IVUS images as a proximal key frame.

[0031] Alternatively or additionally, in any embodiment of the at least one machine-readable storage device, the instructions, in response to being executed by the processor, may cause the processor to receive an indication of the proximal IVUS frame and the distal IVUS frame from an input device.

[0032] Alternatively or additionally, in any of the embodiments of the at least one machine-readable storage device described above, the series of IVUS images includes a plurality of IVUS image frames, and identifying one of the plurality of internal IVUS frames having a smooth lumen area less than or equal to the minimum smooth lumen area as a smooth lumen frame includes designating each IVUS image of the plurality of IVUS images that is positioned between the proximal IVUS frame and the distal IVUS frame as an internal IVUS frame, identifying the minimum smooth lumen area among the plurality of internal IVUS frames, identifying one or more internal IVUS frames that have a smooth lumen area equal to the minimum smooth lumen area, and designating an internal IVUS frame of the identified one or more internal IVUS frames that is centered relative to the proximal IVUS frame and the distal IVUS frame as a minimum smooth lumen frame. [Brief explanation of the drawings]

[0033] [Figure 1] FIG. 1 illustrates one aspect of the subject matter according to one embodiment. [Figure 2] FIG. 2 illustrates one aspect of the subject matter according to one embodiment. [Figure 3A] FIG. 3A illustrates one aspect of the subject matter according to one embodiment. [Figure 3B] FIG. 3B illustrates one aspect of the subject matter according to one embodiment. [Figure 4] FIG. 4 illustrates an IVUS image visualization system 400 according to an embodiment of the present disclosure. [Figure 5] FIG. 5 illustrates one aspect of the subject matter according to one embodiment. [Figure 6] FIG. 6 illustrates one aspect of the subject matter according to one embodiment. [Figure 7] FIG. 7 illustrates one aspect of the subject matter according to one embodiment. [Figure 8] FIG. 8 illustrates one aspect of the subject matter according to one embodiment. [Figure 9] FIG. 9 illustrates one aspect of the subject matter according to one embodiment. [Figure 10] FIG. 10 illustrates one aspect of the subject matter according to one embodiment. [Figure 11] FIG. 11 illustrates a computer-readable storage medium 1100 according to one embodiment. [Figure 12] FIG. 12 shows a schematic diagram of a machine 1200 in the form of a computer system upon which a set of instructions for causing the machine to perform any one or more of the methods described herein may be executed, according to an exemplary embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0034] The foregoing has outlined broadly the features and technical advantages of the present disclosure so that the detailed description thereof may be better understood. It will be appreciated by those skilled in the art that the disclosed embodiments may be readily utilized as a basis for modifying or designing other structures for carrying out the same purposes of the present disclosure. The novel features of the present disclosure, both as to its organization and operation, together with further objects and advantages, may be better understood from the following description when considered in conjunction with the accompanying drawings. It should be noted, however, that each drawing is provided for purposes of illustration and description and is not intended to limit the disclosure. To readily identify an element or description of a process, the most significant digit(s) in a reference number refers to the figure in which the element is first introduced.

[0035] As noted above, the present disclosure relates to IVUS images of a patient and a lumen (e.g., a blood vessel) and to processing IVUS recordings, in other words, processing a series of IVUS images. Accordingly, the following describes an exemplary IVUS imaging system, a patient's blood vessel, and a series of IVUS images.

[0036] Suitable IVUS imaging systems include, but are not limited to, one or more transducers disposed at the distal end of a catheter configured and arranged for percutaneous insertion into a patient. Examples of IVUS imaging systems with catheters can be found, for example, in U.S. Patent Nos. 7,246,959, 7,306,561, and 6,945,938, as well as U.S. Patent Application Publication Nos. 2006 / 0100522, 2006 / 0106320, 2006 / 0173350, 2006 / 0253028, 2007 / 0016054, and 2007 / 0038111, all of which are incorporated herein by reference.

[0037] 1 illustrates one embodiment of an IVUS imaging system 100. The IVUS imaging system 100 includes a catheter 102 that can be coupled to a control system 104. The control system 104 can include, for example, a processor 106, a pulse generator 108, and a drive unit 110. The pulse generator 108 forms electrical pulses that can be input to one or more transducers (not shown) disposed within the catheter 102.

[0038] In some embodiments, mechanical energy from the drive unit 110 may be used to drive an imaging core (not shown) disposed within the catheter 102. In at least some embodiments, electrical signals transmitted from one or more transducers may be input to the processor 106 for processing. In at least some embodiments, the processed electrical signals from the one or more transducers may be used to form a series of images, as described in more detail below. For example, a scan converter may be used to map scan line samples (e.g., radial scan line samples, etc.) onto a two-dimensional Cartesian grid, which may be used as the basis for a series of IVUS images that may be displayed to a user.

[0039] In at least some embodiments, the processor 106 may also be used to control the functions of one or more of the other components of the control system 104. For example, the processor 106 may be used to control the frequency and / or duration of the electrical pulses transmitted from the pulse generator 108 and the rotation speed of the imaging core by the drive unit 110. Also, if the IVUS imaging system 100 is configured for automatic pullback, the drive unit 110 may control the speed and / or length of the pullback.

[0040] 2 shows an image 200 of a patient's blood vessel 202. An IVUS imaging system (e.g., IVUS imaging system 100, etc.) is used to obtain a series of images or "recordings" of a blood vessel, such as blood vessel 202. For example, an IVUS catheter (e.g., catheter 102) is inserted into blood vessel 202, and the recordings or series of IVUS images are obtained as catheter 102 is withdrawn from distal end 204 to proximal end 206. Catheter 102 may be withdrawn manually or automatically (e.g., under the control of drive unit 110, etc.).

[0041] 3A and 3B show two-dimensional (2D) representations of IVUS images of a blood vessel 202. For example, FIG. 3A shows multiple IVUS images 300a of a longitudinal view of an IVUS recording of the blood vessel 202 between the proximal end 206 and the distal end 204.

[0042] 3B shows an image frame 300b of an on-axial (or short-axis) view of the blood vessel 202 at the location 302. In other words, the image frame 300b is a frame or an image from a series of IVUS images that may be acquired between the distal end 204 and the proximal end 206, as described herein. As discussed above, the present disclosure provides systems and techniques for processing raw IVUS images to identify regions of interest, such as, for example, start and end points that include frames of interest within a series of IVUS images.

[0043] For example, IVUS image 300a shows an entire series of IVUS images taken from blood vessel 202 between distal end 204 and proximal end 206. However, not all of these images may be of interest to a physician. This disclosure provides for identifying "key frames," such as proximal key frames, distal key frames, and minimum key frames.

[0044] FIG. 4 illustrates an IVUS image visualization system 400 according to some embodiments of the present disclosure. Generally, the IVUS image visualization system 400 is a system for processing, annotating, and presenting multiple IVUS images. The IVUS image visualization system 400 may be implemented in a commercially available IVUS guidance or navigation system, such as the AVVIGO® guidance system available from Boston Scientific®. The present disclosure provides an advantage over conventional IVUS navigation systems in that automatic keyframe detection reduces the time required to treat a patient. For example, the present disclosure may be implemented in an IVUS navigation system used in percutaneous coronary intervention (PCI). The present disclosure may be provided to quickly and automatically provide information to a physician, including graphical information elements that provide more information than raw IVUS images alone. This information (e.g., keyframe identification and graphical representation) may be automatically determined as part of pre-PCI, pre-PCI, or post-PCI while a user (e.g., a physician) is using the system and while the patient is undergoing treatment. For example, when a physician places a stent, the present disclosure can be used to present the physician with an image (e.g., on a display) and provide a navigation framework for the physician to more quickly and easily identify the type, size, and location of the stent, thereby reducing the time the patient is undergoing treatment.

[0045] In some embodiments, the IVUS image visualization system 400 may be implemented as part of the control system 104. Alternatively, the control system 104 may be implemented as part of the IVUS image visualization system 400. As shown, the IVUS image visualization system 400 includes a computing device 402. Optionally, the IVUS image visualization system 400 includes the IVUS imaging system 100 and a display 404.

[0046] The computing device 402 may be any of a variety of computing devices. In some embodiments, the computing device 402 may be incorporated into and / or implemented by the console of the display 404. In some embodiments, the computing device 402 may be a workstation or server communicatively coupled to the IVUS imaging system 100 and / or the display 404. In still other embodiments, the computing device 402 may be provided by a cloud-based computing device, such as a computing means as a service system accessible via a network (e.g., the Internet, an intranet, a wide area network, etc.). The computing device 402 may include a processor 406, a memory 408, input and / or output (I / O) devices 410, a network interface 412, and an IVUS imaging system acquisition circuit 414.

[0047] Processor 406 may include circuitry or processor logic, such as, for example, any of a variety of commercially available processors. In some examples, processor 406 may include multiple processors, a multithreaded processor, a multi-core processor (where multiple cores may coexist on the same die or may be separate), and / or some other type of multi-processor architecture in which multiple physically separate processors are linked in some way. Also, in some examples, processor 406 may include a graphics processing portion, as well as dedicated memory, multithreaded processing, and / or some other parallel processing capability. In some examples, processor 406 may be an application-specific integrated circuit (ASIC) or a field-programmable integrated circuit (FPGA).

[0048] Memory 408 may include logic portions, portions of which may include an array of integrated circuits to form non-volatile memory or a combination of non-volatile and volatile memory for persistent storage of data. Memory 408 may be based on any of a variety of technologies. In particular, the array of integrated circuits included in memory 120 may be arranged to form one or more types of memory, such as, for example, dynamic random access memory (DRAM), NAND memory, NOR memory, etc.

[0049] I / O device 410 may be any of a variety of devices for receiving input and / or providing output. For example, I / O device 410 may include a keyboard, a mouse, a joystick, a foot pedal, a display, a touch-enabled display, a tactile feedback device, an LED, etc.

[0050] The network interface 412 may include logic and / or functionality to support communications interfaces. For example, the network interface 412 may include one or more interfaces operating according to various communications protocols or standards for communicating directly or over a network communications link. Direct communication may occur through the use of communications protocols or standards set forth in one or more industry standards (including derivatives and variations). For example, the network interface 412 may facilitate communication over buses such as Peripheral Component Interconnect Express (PCIe®), Non-Volatile Memory Express (NVMe®), Universal Serial Bus (USB), System Management Bus (SMBus®), SAS (e.g., Serial Attached Small Computer System Interface (SCSI)), and Serial AT Attachment (SATA) interfaces. The network interface 412 may also include logic and / or functionality to enable communication over various wired or wireless network standards (e.g., the 502.11 communications standard). For example, the network interface 412 may be configured to support wired communications protocols or standards such as Ethernet. As another example, the network interface 412 may be configured to support wireless communication protocols or standards such as Wi-Fi, Bluetooth, ZigBee, LTE, 5G, etc.

[0051] The IVUS imaging system acquisition circuitry 414 may include circuitry including custom-manufactured or specially programmed circuitry configured to send and receive signals to and from the IVUS imaging system 100 including instructions for an IVUS performance, a display of a series of IVUS images, or a display of one or more frames of an IVUS image.

[0052] The memory 408 may include instructions 416. During operation, the processor 406 may execute the instructions 416 to cause the computing device 402 to receive a record of an "IVUS run" (e.g., from the IVUS imaging system 100) and store the record in the memory 408 as an IVUS image 418. For example, the processor 406 may execute the instructions 416 to receive from the IVUS imaging system 100 an information element including a representation of an IVUS image acquired by the catheter 102 while the catheter 102 is being pulled back from the distal end 204 to the proximal end 206. The IVUS image includes a representation of the anatomy and / or structure of the blood vessel 202, including the vessel wall and plaque. The IVUS image 418 may be stored in a variety of image formats, including a representation of the blood vessel 202, or in a non-image format or data structure. Also, the IVUS image 418 includes several "frames" or individual images that, when represented collinearly, can be used to form an image of the blood vessel 202, for example, as represented by the IVUS images 300a and / or 300b.

[0053] The present disclosure provides for processing the IVUS image to identify a key frame from multiple frames within the IVUS image 418. For example, the present disclosure provides for identifying a distal key frame 420, a proximal key frame 422, and a minimum key frame 424. The processor 406 may identify the minimum key frame 424 by executing the instructions 416. In some examples, the processor 406 may further identify the distal key frame 420 and / or the proximal key frame 422 by executing the instructions 416. However, in other examples, the processor 406 may receive an indication (e.g., via the I / O device 410, etc.) of the distal key frame 420 and / or the proximal key frame 422 by executing the instructions 416. In some embodiments, the processor 406 may identify the distal key frame 420, the proximal key frame 422, and the minimum key frame 424 by executing the instructions 416. The processor 406 may then execute the instructions 416 to receive an indication of the updated distal key frame 420 and / or proximal key frame 422 and re-identify the minimum key frame 424 based on the updated distal key frame 420 and / or proximal key frame 422 as described herein.

[0054] Generally, processor 406 may execute instructions 416 to identify key frames based on raw lumen boundaries and smooth lumen boundaries. Specifically, processor 406 may execute instructions 416 to determine a raw lumen area 426 for a frame in an IVUS image 418. Processor 406 may also execute instructions 416 to determine a smooth lumen area 428 from the raw lumen area 426. In some embodiments, smooth lumen area 428 may be determined based on a moving average filter or an n-sample median filter. As a specific example, processor 406 may execute instructions 416 to determine smooth lumen area 428 based on a 21-sample median filter applied to IVUS image 418 and raw lumen area 426. Furthermore, in some embodiments, smooth lumen area 428 may be determined based on a first filter that is an n-sample median filter and a second filter that is an n-distance median filter. This is described in more detail below. In general, however, if the IVUS image 418 is acquired through a manual pullback operation, the smoothed lumen area 428 may be determined based on a single filter (e.g., an n-sample median filter). On the other hand, if the IVUS image 418 is acquired through an automatic pullback operation, the smoothed lumen area 428 may be determined based on multiple filters (e.g., an n-sample median filter and an n-distance median filter).

[0055] The processor 406 may execute instructions 416 to determine a minimum area subset 430 of IVUS images from frames in the IVUS images 418 that are collinear between the distal keyframe 420 and the proximal keyframe 422 by identifying a smooth lumen frame 432 based on the smooth lumen area 428, and then identify a minimum keyframe 424 from frames in the minimum area subset 430 of IVUS images based on the raw lumen area 426. This provides the advantage that errors in processing the IVUS images 418 to determine the raw lumen area 426 (e.g., automatic boundary detection errors, etc.) do not lead to a misidentification of the minimum keyframe 424.

[0056] In some embodiments, the processor 406 may execute instructions 416 to identify the distal keyframes 420 and the proximal keyframes 422 based on plaque burden, i.e., the ratio of the raw lumen area 426 to the vessel area 434. In such an example, the processor 406 may execute instructions 416 to determine the vessel area 434 for a frame in the IVUS image 418 and determine the distal keyframes 420 and the proximal keyframes 422 based on the ratio of the raw lumen area 426 to the vessel area 434 or the ratio of the smooth lumen area 428 to the smooth vessel area 436, as described in more detail below.

[0057] 5 illustrates a logic flow 500 for identifying key frames from an IVUS recording, according to some embodiments of the present disclosure. The logic flow 500 may be implemented by the IVUS image visualization system 400. For clarity of presentation, the logic flow 500 will be described below with reference to the IVUS image visualization system 400. However, the logic flow 500 may also be implemented by an IVUS guidance system different from the IVUS image visualization system 400.

[0058] The logic flow 500 may begin at block 502. At block 502, "Receive a series of intravascular ultrasound (IVUS) images of a patient's blood vessel," a series of IVUS images acquired via an IVUS catheter percutaneously inserted into the patient's blood vessel may be received. For example, an information element including a representation of the IVUS image 418 may be received from the IVUS imaging system 100 at a location where the catheter 102 is (or was) percutaneously inserted into the blood vessel 202. The IVUS image 418 may include frames of images representing images acquired while the catheter 102 is being retracted from the distal end 204 to the proximal end 206. The processor 406 may execute instructions 416 to receive the information element including the representation of the IVUS image 418 from the IVUS imaging system 100, or in some cases directly from the catheter 102.

[0059] Next, proceeding to block 504, "Determine the lumen area represented in each of the IVUS images," the lumen area represented in each frame of the IVUS images may be determined. For example, the raw lumen area 426 represented in each frame of the IVUS image 418 may be determined. The processor 406 may execute the instructions 416 to determine the raw lumen area 426 of the IVUS image 418. Further, in some embodiments, in block 504, the processor 406 may execute the instructions 416 to determine the vessel area 434 of the IVUS image 418.

[0060] For example, FIG. 6 illustrates an image 600 of an axial view of a frame of IVUS images 418 depicting a portion of a blood vessel 202. A vessel area 434 and a raw lumen area 426 may be determined for the portion of the blood vessel 202 represented in the depicted frame. Proceeding to block 506, "Smooth Raw Lumen Area," the raw lumen area may be smoothed. For example, the raw lumen area may be smoothed. In some embodiments, the processor 406 may execute instructions 416 to determine a smoothed lumen area 428 based on the raw lumen area 426 and an n-sample median filter. The smoothed lumen area 428 may be based on a 21-sample median filter applied to the raw lumen area 426. In other embodiments, the processor 406 may execute instructions 416 to determine a smoothed lumen area 428 based on the raw lumen area 426, an n-sample median filter, and an n-distance median filter. For example, smoothed lumen area 428 may be determined from raw lumen area 426 and an n-sample median filter (e.g., 21 samples, etc.). Subsequently, a "smoother" smoothed lumen area 428 may be determined from smoothed lumen area 428 and an n-distance median filter. The n-distance median filter may be a 1 millimeter (mm) median filter, a 2 mm median filter, a 3 mm median filter, or a 4 mm median filter. If IVUS image 418 is based on an automatic pullback IVUS run, then "smoother" smoothed lumen area 428 may be used.

[0061] Logic flow 500 may then proceed to decision block 508, "Are Distal and Proximal Keyframes Known?", where a determination is made as to whether distal keyframe 420 and proximal keyframe 422 are known. For example, processor 406 may execute instructions 416 to determine whether an indication of distal keyframe 420 and proximal keyframe 422 has been received (e.g., via I / O device 410, etc.). From decision block 508, logic flow 500 may proceed to block 510 or to block 512. Logic flow 500 may proceed from decision block 508 to block 510 based on a determination at decision block 508 that distal keyframe 420 and proximal keyframe 422 are not known. Logic flow 500 may also proceed from decision block 508 to block 512 based on a determination at decision block 508 that distal keyframe 420 and proximal keyframe 422 are known.

[0062] In block 510, "Identify Distal and / or Proximal Key Frames," distal key frames 420 and / or proximal key frames 422 may be determined. In some examples, both distal key frames 420 and proximal key frames 422 may be determined in block 510. In some cases, an indication may have been received for one of the key frames (e.g., distal key frame 420 or proximal key frame 422), in which case the other key frame may be identified in block 510. Generally, distal key frames 420 and proximal key frames 422 may be identified based in part on smooth lumen area 428. However, specific examples of determining distal key frames 420 and proximal key frames 422 are provided below. For example, Figures 7 and 8 show logic flows 700 and 800, respectively, that may be implemented to identify distal key frames 420 and proximal key frames 422 of an IVUS image 418 acquired based on a manual pullback IVUS run (e.g., logic flow 700) or an automatic pullback IVUS run (e.g., logic flow 800).

[0063] Proceeding next to block 512, "Identify smooth lumen frames from IVUS images," frames may be identified from the series of IVUS images and designated as smooth lumen frames. For example, processor 406 may execute instructions 416 to identify smooth lumen frames 432 from IVUS images 418 based on distal key frames 420, proximal key frames 422, and the smooth lumen area 428 of each IVUS image 418. In some embodiments, processor 406 may execute instructions 416 to identify a frame of IVUS image 418 that is located between distal key frame 420 and proximal key frame 422 and has the smallest smooth lumen area 428. If multiple frames of IVUS image 418 all have the same smooth lumen area 428, i.e., all have the smallest smooth lumen area 428, processor 406 may identify an intermediate frame as smooth lumen frame 432.

[0064] Proceeding to block 514, "Identify a subset of IVUS images including a number of collinear frames with the smooth lumen frame," a subset of IVUS images may be identified. Specifically, a minimum area subset 430 of IVUS images may be determined from the IVUS image 418 based on the smooth lumen frame 432. For example, by executing instructions 416, processor 406 may identify a number of frames of the IVUS image 418 that are collinear with the smooth lumen frame 432 (e.g., at least two, at least eleven, or a number of frames corresponding to a selected distance along the vessel 202).

[0065] In some embodiments, for example, when the IVUS image 418 is acquired based on a manual pullback IVUS run, the processor 406 executes instructions 416 to identify (or designate, mark, or flag) the smooth lumen frame 432 and m (e.g., 10, or 5-15, etc.) frames that are collinearly distal and collinearly proximal to the smooth lumen frame as a minimum regional subset 430 of the IVUS image.

[0066] In some embodiments, for example, if the IVUS image 418 is acquired based on an automatic pullback IVUS run, the processor 406 executes instructions 416 to identify (or designate, mark, or flag) the smooth lumen frame 432 and frames from the IVUS image 430 acquired within an x ​​distance (e.g., 1 mm, 1.5 mm, 2 mm, or 0.5-2 mm, etc.) from the smooth lumen frame 432 as the minimum region subset 430 of the IVUS image.

[0067] In some embodiments, if the distal key frame 420 or the proximal key frame 422 is identified as being included in the minimum region subset 430 of the IVUS image, the minimum region subset 430 of the IVUS image may be truncated to the frame immediately distal to the proximal key frame 422 or to the frame immediately proximal to the distal key frame 420.

[0068] Proceeding next to block 516, "Identify a minimum keyframe from a subset of multiple IVUS images," a frame having a minimum lumen area, i.e., a minimum keyframe, may be identified from the subset of IVUS images and the raw lumen area. For example, minimum keyframe 424 may be identified from smooth lumen frame 432 based on raw lumen area 426. Processor 406 may execute instructions 416 to identify a frame within minimum region subset 430 of IVUS images having a minimum raw lumen area 426.

[0069] FIG. 7 illustrates a logic flow 700 that may be implemented to identify distal key frames 420 and / or proximal key frames 422 of IVUS images 418 acquired based on a manual IVUS run. As described above, in some embodiments, logic flow 500 may implement logic flow 700 at block 510. Logic flow 700 may begin at block 702. At block 702, "Identify first frame in recording as a distal key frame," the first frame in the IVUS recording may be designated or identified as a distal key frame. For example, processor 406 may execute instruction 416 to identify the first frame of IVUS image 418 as distal key frame 420. Next, proceeding to block 704, "Identify last frame in recording as a proximal key frame," the last frame in the IVUS recording may be designated or identified as a proximal key frame. For example, processor 406 may execute instruction 416 to identify the last frame of IVUS image 418 as proximal key frame 422.

[0070] 8 illustrates a logic flow 800 that may be implemented to identify distal key frames 420 and / or proximal key frames 422 based on the smooth lumen area 428 of IVUS images 418 acquired based on a manual IVUS performance. As described above, in some embodiments, logic flow 500 may implement logic flow 800 at block 510. Logic flow 800 may begin at block 802. At block 802, "Identify Initial Distal Search Frame," an initial distal search frame may be identified. For example, processor 406 may execute instructions 416 to identify either (1) the first frame in the series of IVUS images 418 or (2) the most distal frame in the series of IVUS images 418 as the initial distal search frame. Here, the smooth lumen area 428 of the most distal frame is less than 0.5 mm relative to the smooth lumen area 428 of the adjacent distal frame. 2 The area is less than the area of ​​the

[0071] Proceeding to block 804, "Identify initial proximal search frame," an initial proximal search frame may then be identified. For example, processor 406 may execute instructions 416 to identify as the initial proximal search frame: (1) the most distal frame relative to a specified distance (e.g., 1 mm, 1.1 mm, or 0.5 mm to 1.5 mm, etc.) distal from the last frame in the series of IVUS images 418; (2) the most proximal frame before the start of the guide catheter; or (3) the most distal frame relative to consecutive frames having a descending smooth lumen area 428.

[0072] Next, proceeding to block 806, "Identify a frame between the initial proximal search frame and the initial distal search frame that is located within a first distance from the frame with the smallest smooth lumen area and has the smallest raw lumen area as a center search frame," a frame between the initial proximal search frame and the initial distal search frame that is located within a first distance from the frame with the smallest smooth lumen area and has the smallest raw lumen area may be identified as the center search frame. For example, processor 406 may execute instructions 416 to identify and designate as the center search frame a frame between the initial proximal search frame and the initial distal search frame that is located within a first distance (e.g., 1 mm, 1.1 mm, 0.5 mm to 1.5 mm, etc.) from the frame with the smallest smooth lumen area 428 and has the smallest raw lumen area 426. As described above, in some examples, the smooth lumen area may be determined based on multiple types of sampling filters. In other words, a smooth lumen area may be determined, and a more smoothed lumen area may be determined. In some examples, the center search frame identified in block 806 may be identified based on the smoothed lumen area and the raw lumen area, as described above.

[0073] Next, proceeding to block 808, "Smooth vessel area," the vessel area may be smoothed. For example, processor 406 may execute instructions 416 to determine smooth vessel area 436 based on vessel area 434 and an n-sample median filter. Next, proceeding to block 810, "Identify frames at least a second distance from the central search frame, having smooth plaque load and raw plaque load less than or equal to thresholds, as distal and proximal keyframes," the frames closest to the central search frame, having smooth plaque load and raw plaque load less than or equal to 50%, may be identified as distal and proximal keyframes. Processor 406 may execute instructions 416 to identify frames distal to the central search frame by at least a specified distance and having smooth plaque loads (e.g., smooth lumen area 428 relative to smooth vessel area 436) less than or equal to a threshold (e.g., 50%, 60%, or 40-60%) as distal keyframes 420. In some examples, the processor 406 may execute the instructions 416 to identify the initial distal search frame as the distal key frame 420 if it determines that there are no frames distal to the central search frame that have a raw plaque load and a smooth plaque load of 50% or less.

[0074] Similarly, processor 406 may execute instructions 416 to identify a frame at least a specified distance proximal from the central search frame that has a smooth plaque load (e.g., smooth lumen area 428 relative to smooth vessel area 436) at or below a threshold (e.g., 50%, 60%, or 40-60%) as proximal key frame 422. In some examples, if processor 406 executes instructions 416 to determine that no frame with a raw plaque load and smooth plaque load at or below 50% is proximal from the central search frame, processor 406 may identify as proximal key frame 422 either (1) the last frame at the time of execution or (2) the more distal frame immediately distal to the guide catheter.

[0075] 9 illustrates an annotated image 900 representing annotation of an image 200 showing a blood vessel 202, according to some embodiments of the present disclosure. As described herein, the present disclosure provides systems and techniques for automatically (e.g., without user input) identifying keyframes, such as a distal keyframe 420, a proximal keyframe 422, and a minimum keyframe 424. In some examples, an image of a patient's blood vessel 202 may be annotated with indications of the keyframes as well as an indication of the starting frame of an IVUS run. For example, the processor 406 may execute the instructions 416 to generate graphical information elements to be rendered and displayed on the display 404 to represent the annotated image 900. As illustrated, the annotated image 900 includes depictions of the blood vessel 202, the distal end 204, the proximal end 206, the distal keyframe 420, the proximal keyframe 422, and the minimum keyframe 424.

[0076] 10 illustrates a graphical element 1000 that may be generated and presented to a user according to some embodiments of the present disclosure. The processor 406 may execute the instructions 416 to generate the graphical element 1000 including an animated depiction of the vessel area 434 and the live lumen area 426 along with the distal keyframe 420, the proximal keyframe 422, and the minimum keyframe 424.

[0077] The annotated image 900 shown in FIG. 9 and / or the graphic element 1000 shown in FIG. 10 may be generated by the IVUS image visualization system 400 and displayed on the display 404 as part of the PCI as outlined above.

[0078] 11 illustrates a computer-readable storage medium 1100. The computer-readable storage medium 1100 may include any non-transitory computer-readable or machine-readable storage medium, such as an optical storage medium, a magnetic storage medium, or a semiconductor storage medium. In various embodiments, the computer-readable storage medium 1100 may include an article of manufacture. In some embodiments, the computer-readable storage medium 1100 may store computer-executable instructions 1102 executable by a circuit (e.g., processor 106, processor 406, IVUS imaging system acquisition circuitry 414, etc.). For example, the computer-executable instructions 1102 may include instructions for implementing the operations described with respect to instructions 416, logic flow 500, logic flow 700, logic flow 800, annotated image 900, and / or graphic element 1000. Examples of computer-readable storage medium 1100 or machine-readable storage media may include any tangible medium capable of storing electronic data, including volatile or non-volatile memory, removable or non-removable memory, erasable or non-erasable memory, writable or rewritable memory, etc. Examples of computer-executable instructions 1102 may include any suitable type of code, such as source code, compiled code, interpreted code, executable code, static code, dynamic code, object-oriented code, visual code, etc.

[0079] 12 illustrates a schematic diagram of a machine 1200 in the form of a computer system within which a set of instructions may be executed to cause the machine to perform any one or more of the methods described herein. Specifically, FIG. 12 illustrates a schematic diagram of a machine 1200 in the exemplary form of a computer system within which may be executed instructions 1208 (e.g., software, programs, applications, applets, apps, or other executable code) to cause the machine 1200 to perform any one or more of the methods described herein. For example, the instructions 1208 may cause the machine 1200 to perform logic flow 500 of FIG. 5, logic flow 700 of FIG. 7, logic flow 800 of FIG. 8, etc. More generally, the instructions 1208 may cause the machine 1200 to automatically determine key frames pre-, pre-, or post-PCI using IVUS. The present disclosure provides specific and distinct implementations for identifying key frames (e.g., distal key frame 420, proximal key frame 422, and / or minimum key frame 424), which are significant improvements over the prior art. In particular, the present disclosure provides an improvement over computational techniques in that key frames (e.g., particularly minimum key frame 424) are identified while the IVUS imaging system is in use, and key frames can be re-identified based on updated factors (e.g., a user moving distal key frame 420 or proximal key frame 422).

[0080] The instructions 1208 transform a general, unprogrammed machine 1200 into a specific machine 1200 programmed to perform the functions described and illustrated in a specific manner. In alternative embodiments, the machine 1200 may operate as a standalone device or may be coupled (e.g., networked) to other machines. In a networked deployment, the machine 1200 may operate as a server or a client machine in a server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine 1200 may include, but is not limited to, a server computer, a client computer, a personal computer (PC), a tablet computer, a laptop computer, a netbook, a set-top box (STB), a PDA, an entertainment media system, a mobile phone, a smartphone, a mobile device, a wearable device (e.g., a smart watch), a smart home device (e.g., a smart appliance), other smart devices, a web appliance, a network router, a network switch, a network bridge, or any machine capable of sequentially or otherwise executing instructions 1208 that specify operations to be performed by the machine 1200. Additionally, although only a single machine 1200 is illustrated, the term "machine" is also intended to include a collection of machines 1200 that individually or jointly execute instructions 1208 to perform any one or more of the methodologies described herein.

[0081] Machine 1200 may include processor 1202, memory 1204, and I / O components 1242, which may be configured to communicate with each other via a bus 1244 or the like. In an exemplary embodiment, processor 1202 (e.g., a central processing unit (CPU), a reduced instruction set computing (RISC) processor, a complex instruction set computing (CISC) processor, a graphics processing unit (GPU), a digital signal processor (DSP), an ASIC, a radio frequency integrated circuit (RFIC), another processor, or any suitable combination thereof) may include, for example, processor 1206 and processor 1210, which may execute multiple instructions 1208. The term "processor" is intended to include a multi-core processor, which may include two or more independent processors (sometimes referred to as "cores") capable of simultaneously executing multiple instructions. While FIG. 12 shows multiple processors 1202, machine 1200 may include a single processor with a single core, a single processor with multiple cores (e.g., a multi-core processor), multiple processors with a single core, multiple processors with multiple cores, or any combination thereof.

[0082] Memory 1204 may include main memory 1212, static memory 1214, and storage unit 1216, which are accessible to processor 1202 via bus 1244 or the like. Main memory 1204, static memory 1214, and storage unit 1216 store instructions 1208 that embody any one or more of the methods or functions described herein. Also, instructions 1208 may reside, completely or partially, within main memory 1212, static memory 1214, within machine-readable medium 1218 in storage unit 1216, within at least one of processors 1202 (e.g., within a processor's cache memory), or any suitable combination thereof during their execution by machine 1200.

[0083] I / O components 1242 may include a wide variety of components for receiving input, providing output, generating output, transmitting information, exchanging information, capturing measurements, etc. The specific I / O components 1242 included in a particular machine will depend on the type of machine. For example, a portable device such as a mobile phone will likely include a touch input device or other such input mechanism, while a headless server machine will likely not include such a touch input device. Note that I / O components 1242 may also include many other components not shown in FIG. 12 . I / O components 1242 are grouped according to function solely for ease of description below, and this grouping is not intended to be limiting. In various exemplary embodiments, I / O components 1242 may include output components 1228 and input components 1230. Output components 1228 may include visual components (e.g., a display such as a plasma display panel (PDP), light-emitting diode (LED) display, liquid crystal display (LCD), projector, or cathode ray tube (CRT)), acoustic components (e.g., speakers), tactile components (e.g., vibration motors, resistive mechanisms), other signal generators, etc. Input components 1230 may include alphanumeric input components (e.g., a keyboard, a touchscreen configured to receive alphanumeric input, a photo-optical keyboard, or other alphanumeric input component), point-based input components (e.g., a mouse, touchpad, trackball, joystick, motion sensor, or other pointing device), tactile input components (e.g., physical buttons, a touchscreen that provides the position and / or force of a touch or touch gesture, or other tactile input component), audio input components (e.g., a microphone), etc.

[0084] In further exemplary embodiments, I / O component 1242 may include a biometric component 1232, a motion component 1234, an environmental component 1236, or a position component 1238, among a wide variety of other components. For example, biometric component 1232 may include components for detecting facial expressions (e.g., hand expressions, facial expressions, vocal expressions, gestures, or eye tracking), measuring biosignals (e.g., blood pressure, heart rate, body temperature, sweat, or brain waves), identifying people (e.g., voice identification, retinal identification, face identification, fingerprint identification, or brainwave-based identification), etc. Motion component 1234 may include an acceleration sensor component (e.g., an accelerometer), a gravity sensor component, a rotation sensor component (e.g., a gyroscope), etc. The environmental components 1236 may include, for example, an illuminance sensor component (e.g., a photometer), a temperature sensor component (e.g., one or more thermometers that detect ambient temperature), a humidity sensor component, a pressure sensor component (e.g., a barometer), an acoustic sensor component (e.g., one or more microphones that detect background noise), a proximity sensor component (e.g., an infrared sensor that detects nearby objects), a gas sensor (e.g., a gas detection sensor that detects concentrations of harmful gases or measures pollutants in the air for safety purposes), or other components that may provide an indication, measurement, or signal corresponding to the surrounding physical environment. The position component 1238 may include a location sensor component (e.g., a GPS receiver component), an altitude sensor component (e.g., an altimeter or barometer that detects air pressure from which altitude can be derived), an orientation sensor component (e.g., a magnetometer), etc.

[0085] Communication may be achieved using a wide variety of technologies. I / O component 1242 may include a communication component 1240 operable to couple machine 1200 to network 1220 or device 1222 via connection 1224 and connection 1226, respectively. For example, communication component 1240 may include a network interface component or other suitable device for interfacing with network 1220. In further embodiments, communication component 1240 may include a wired communication component, a wireless communication component, a cellular communication component, a near-field communication (NFC) component, a Bluetooth® component (e.g., Bluetooth® Low Energy), a Wi-Fi® component, and other communication components for communicating via other modalities. Device 1222 may be another machine or any of a wide variety of peripheral devices (e.g., a peripheral device connected via USB).

[0086] Further, the communication component 1240 may detect an identifier or may include a component operable to detect an identifier. For example, the communication component 1240 may include a radio frequency identification (RFID) tag reader component, an NFC smart tag detection component, an optical reader component (e.g., an optical sensor for detecting one-dimensional barcodes such as Universal Product Code (UPC) barcodes, multidimensional barcodes such as Quick Response (QR) Code, Aztec Code, Data Matrix, Dataglyph, MaxiCode, PDF417, Ultra Code, UCC RSS-2D barcodes, and other optical codes), or an acoustic detection component (e.g., a microphone for identifying tagged audio signals). Additionally, various information, such as location via Internet Protocol (IP) geolocation, location via Wi-Fi signal triangulation, location by detection of NFC beacon signals that may indicate a particular location, may be derived via the communication component 1240.

[0087] Various memories (i.e., memory 1204, main memory 1212, static memory 1214, and / or memory of processor 1202) and / or storage unit 1216 may store one or more sets of instructions and data structures (e.g., software) that embody or are utilized by any one or more of the methods or functions described herein. These instructions (e.g., instructions 1208), when executed by processor 1202, cause various operations to implement the disclosed embodiments.

[0088] As used herein, the terms “machine storage medium,” “device storage medium,” and “computer storage medium” mean the same thing and may be used interchangeably in this disclosure. These terms refer to single or multiple storage devices and / or media (e.g., centralized or distributed databases, and / or associated caches and servers) that store executable instructions and / or data. Accordingly, these terms are intended to include, but are not limited to, solid-state memory and magneto-optical media, including memory internal or external to a processor. Specific examples of machine storage media, computer storage media, and / or device storage media include, for example, non-volatile memory, including semiconductor memory devices such as erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), FPGAs, and flash memory devices; magnetic disks, such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The terms “machine storage medium,” “computer storage medium,” and “device storage medium” specifically exclude carrier waves, modulated data signals, and other such media, at least some of which are encompassed under the term “signal media,” discussed below.

[0089] In various exemplary embodiments, one or more portions of network 1220 may be an ad-hoc network, an intranet, an extranet, a VPN, a LAN, a WLAN, a WAN, a WWAN, a MAN, the Internet, a portion of the Internet, a portion of the PSTN, a plain old telephone service (POTS) network, a cellular telephone network, a wireless network, a Wi-Fi network, other types of networks, or a combination of two or more such networks. For example, network 1220 or portions of network 1220 may include a wireless or cellular network. Connection 1224 may be a code division multiple access (CDMA) connection, a Global System for Mobile Communications (GSM) connection, or other type of cellular or wireless connection. In this example, connection 1224 may implement any of various types of data transfer technologies, such as single-carrier radio transmission technology (1xRTT), Evolution Data Optimized (EVDO) technology, General Packet Radio Service (GPRS) technology, Enhanced Data Rates for GSM Evolution (EDGE) technology, Third Generation Partnership Project (3GPP) including 3G, Fourth Generation Wireless (4G) networks, Universal Mobile Telecommunications System (UMTS), High Speed ​​Packet Access (HSPA), Worldwide Interoperability for Microwave Access (WiMAX), Long Term Evolution (LTE) standards, others defined by various standards-setting bodies, other long-range protocols, or other data transfer technologies.

[0090] The instructions 1208 may be transmitted and received over the network 1220 using a transmission medium via a network interface device (e.g., a network interface component included in the communications component 1240) and utilizing any one of several well-known transfer protocols (e.g., Hypertext Transfer Protocol (HTTP)). Similarly, the instructions 1208 may be transmitted and received using a transmission medium via a connection 1226 (e.g., a peer-to-peer connection) to the device 1222. The terms “transmission medium” and “signal medium” mean the same thing and may be used interchangeably in this disclosure. The terms “transmission medium” and “signal medium” are intended to include any intangible medium capable of storing, encoding, or carrying the instructions 1208 for execution by the machine 1200 and including digital or analog communications signals or other intangible media for facilitating communication of such software. Accordingly, the terms “transmission medium” and “signal medium” are intended to include any form of modulated data signal, carrier wave, etc. The term “modulated data signal” means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal.

[0091] Terms used in this specification are to be given their ordinary meaning in the relevant art or as indicated by their use in context, except that if an explicit definition is provided, that meaning will control.

[0092] References herein to "one embodiment" or "an embodiment" do not necessarily refer to the same embodiment, but may refer to the same embodiment. Throughout this specification and claims, words such as "comprises," "comprising," and the like are intended to be construed in an inclusive sense, as opposed to an exclusive or exhaustive sense, such as "including but not limited to," unless the context clearly dictates otherwise. Terms used in the singular or plural also include the plural or singular, respectively, unless expressly limited to one or more. Additionally, the words "herein," "above," "below," and similar words, when used in this application, refer to this application as a whole, not to any portion thereof. When a claim uses the word "or" in connection with a list of two or more items, the word encompasses any item in the list, all items in the list, and any combination of items in the list, unless expressly limited to one or the other. Any terms not expressly defined herein have their conventional meanings as commonly understood by those of ordinary skill in the art.

[0093] By using a true model of the anatomy, more accurate surgical planning can be achieved than through statistical modeling. Terms used in this specification are to be given their ordinary meaning in the relevant art or as indicated by their use in context, except that if an explicit definition is provided, that meaning will control.

[0094] References herein to "one embodiment" or "an embodiment" do not necessarily refer to the same embodiment, but may refer to the same embodiment. Throughout this specification and claims, words such as "comprises," "comprising," and the like are intended to be construed in an inclusive sense, as opposed to an exclusive or exhaustive sense, such as "including but not limited to," unless the context clearly dictates otherwise. Terms used in the singular or plural also include the plural or singular, respectively, unless expressly limited to one or more. Additionally, the words "herein," "above," "below," and similar words, when used in this application, refer to this application as a whole, not to any portion thereof. When a claim uses the word "or" in connection with a list of two or more items, the word encompasses any item in the list, all items in the list, and any combination of items in the list, unless expressly limited to one or the other. Any terms not expressly defined herein have their conventional meanings as commonly understood by those of ordinary skill in the art.

Claims

1. 1. A method comprising: receiving a series of intravascular ultrasound (IVUS) images of a blood vessel of a patient, the series of IVUS images including a proximal IVUS frame, a distal IVUS frame, and a plurality of internal IVUS frames; determining a raw luminal area represented in each of the plurality of internal IVUS frames; determining a smoothed lumen area for each of the plurality of internal IVUS frames based on a sampling filter and the raw lumen area; identifying one of the plurality of internal IVUS frames as a smooth lumen frame having a smooth lumen area less than or equal to a minimum smooth lumen area among the plurality of internal IVUS frames; selecting a subset of the plurality of internal IVUS frames including the smooth lumen frame and at least one other internal IVUS frame of the plurality of internal IVUS frames that is collinear with the smooth lumen frame; and identifying an internal IVUS frame of the subset of the plurality of internal IVUS frames having a raw lumen area less than or equal to the lumen area as a minimum key frame; A method for providing

2. The method of claim 1 , wherein the subset of the plurality of internal IVUS frames comprises 21 frames.

3. The method of claim 1 or 2, wherein the subset of the plurality of intra IVUS frames comprises those of the series of IVUS images that represent a distance along the blood vessel.

4. The method according to any one of claims 1 to 3, wherein said distance is equal to or less than 2 millimeters.

5. The method of any one of claims 1 to 4, wherein the plurality of internal IVUS frames are disposed between the proximal IVUS frame and the distal IVUS frame.

6. The series of IVUS images includes a plurality of IVUS image frames, and the method comprises: designating a first frame in the series of IVUS images as a distal keyframe; and designating the last frame in the series of IVUS images as a proximal keyframe; The method of any one of claims 1 to 5, comprising:

7. The method of any one of claims 1 to 6, comprising receiving an indication of the proximal and distal IVUS frames from an input device.

8. the series of IVUS images includes a plurality of IVUS image frames, and identifying one of the plurality of internal IVUS frames having a smooth lumen area equal to or less than a minimum smooth lumen area among the plurality of internal IVUS frames as a smooth lumen frame; designating each IVUS image of the plurality of IVUS images disposed between the proximal IVUS frame and the distal IVUS frame as an internal IVUS frame; identifying the minimum smooth lumen area among the plurality of internal IVUS frames; identifying one or more internal IVUS frames among the plurality of internal IVUS frames having a smooth lumen area equal to the minimum smooth lumen area; and designating an internal IVUS frame of the identified one or more internal IVUS frames that is centrally located relative to the proximal and distal IVUS frames as a minimum smooth lumen frame; The method of claim 7, comprising:

9. 9. The method of claim 1, wherein the sampling filter includes a first sampling filter, and the method comprises determining a smoothed lumen area for each of the plurality of IVUS images based on a second sampling filter different from the first sampling filter and the smoothed lumen area.

10. The series of IVUS images includes a plurality of IVUS image frames, and the method comprises: identifying an initial proximal search frame and an initial distal search frame; identifying an IVUS image frame having the minimum smooth lumen area from among the plurality of IVUS image frames located between the initial proximal search frame and the initial distal search frame; identifying one of the plurality of IVUS image frames located within a first distance from the IVUS image frame and having a minimum live lumen area as a center search frame; identifying one of the plurality of IVUS image frames as a distal key frame, the one being located within a second distance distal to the central search frame and having a smooth plaque burden and a raw plaque burden less than a threshold; and identifying one of the plurality of IVUS image frames located within the second distance proximal from the central search frame and having a smooth plaque burden and a raw plaque burden less than the threshold as a proximal key frame; The method of claim 9 comprising:

11. The method of claim 10 , wherein the threshold value is between 40 percent and 60 percent.

12. 12. The method of claim 10 or 11, wherein the second distance is 5 millimeters or less.

13. The method of any one of claims 10 to 12, wherein the first distance is equal to or less than 1 millimeter.

14. 1. An apparatus comprising:

14. An apparatus comprising: a processor coupled to a memory, the memory including a plurality of instructions executable by the processor, the processor configured to be coupled to an intravascular ultrasound (IVUS) imaging system and configured to execute the plurality of instructions, the plurality of instructions, when executed, causing the processor to perform the method of any one of claims 1 to 13.

15. at least one machine-readable storage device, A machine-readable storage device comprising a plurality of instructions that, when executed by a processor of an intravascular ultrasound (IVUS) imaging system, causes the processor to perform the method of any one of claims 1 to 13.

Images