Three-dimensional imaging of coronary arteries

Abstract

A method for three-dimensional (3D) imaging of coronary arteries includes acquiring a sequence of two-dimensional (2D) intravascular (IV) images of a coronary artery, extracting a set of IV longitudinal images from the sequence of IV images, detecting a lumen border of the coronary artery and a media-adventitia (MA) border of the coronary artery based on the set of IV longitudinal images, estimating a sequence of geometric mass centers based on the lumen border and the MA border, estimating a 2D motion signal from the sequence of geometric mass centers, estimating a sequence of rotations for the sequence of 2D IV images based on the 2D motion signal, generating a sequence of transformed IV frames from the sequence of 2D IV images based on the sequence of rotations and the 2D motion signal, and reconstructing a 3D image from the sequence of transformed IV frames.

Description

THREE-DIMENSIONAL IMAGING OF CORONARY ARTERIES TECHNICAL FIELD

[0001] The present disclosure generally relates to medical imaging, and particularly, to three- dimensional intravascular imaging. BACKGROUND ART

[0002] Heart disease is a leading cause of death around the globe, which is afflicted by a variety of heart defects, the most frequent of which is coronary atherosclerosis. In this regard, non- invasive imaging technologies lack the ability to assess atherosclerotic tissues quantitatively. As a result, intravascular imaging has become widespread.

[0003] Various imaging techniques of intravascular (IV) imaging are frequently used for evaluating and treating atherosclerosis. Fluoroscopic imaging, optical coherence tomography (OCT), intravascular optical coherence tomography (IVOCT), and intravascular ultrasound (IVUS) are some examples of imaging techniques. Ultrasonic echoes are used in IVUS to create images of blood vessels and surrounding areas. IVUS imaging can distinguish between media and lumen borders, as well as searching for different types of atherosclerotic tissues per frame.

[0004] Three-dimensional (3D) reconstruction of IVUS / IVOCT images makes it possible to study treatment of atherosclerosis in a longitudinal view and also to examine dynamic characteristics of atherosclerosis plaques. Unfortunately, due to movement of blood vessels around an IVUS catheter and external factors such as cardiac and breathing signals, a sequence of IVUS images may lack apparent 3D information. Additional external imaging such as angiography has been used to overcome this problem. However, this solution makes the imaging process difficult, time-consuming, and expensive. There is, therefore, a need for a cost-efficient method for 3D image reconstruction of coronary arteries that may provide useful information for studying characteristics of atherosclerosis plaques without a need for additional time-consuming processes. SUMMARY OF THE DISCLOSURE

[0005] This summary is intended to provide an overview of the subject matter of this patent, and is not intended to identify essential elements or key elements of the subject matter, nor is it intended to be used to determine the scope of the claimed implementations. The proper scopeof this patent may be ascertained from the claims set forth below in view of the detailed description below and the drawings.

[0006] In one general aspect, the present disclosure describes an exemplary method for three- dimensional (3D) imaging of coronary arteries. An exemplary method may include acquiring a sequence of two-dimensional (2D) intravascular (IV) images of a coronary artery, extracting a set of IV longitudinal images from the sequence of 2D IV images, detecting a lumen border of the coronary artery and a media-adventitia (MA) border of the coronary artery based on the set of IV longitudinal images, estimating a sequence of geometric mass centers of the coronary artery based on the lumen border and the MA border, estimating a 2D motion signal of the coronary artery from the sequence of geometric mass centers, estimating a respective rotation of a sequence of rotations for each respective 2D IV image of the sequence of 2D IV images with respect to a previous 2D IV image of the sequence of 2D IV images based on the 2D motion signal, generating a sequence of transformed IV frames from the sequence of 2D IV images based on the sequence of rotations and the 2D motion signal, and reconstructing a 3D image of the coronary artery from the sequence of transformed IV frames.

[0007] An exemplary one or more medical imaging modalities may be utilized for acquiring the sequence of 2D IV images. An exemplary 3D image may be reconstructed based on an imaging speed of the one or more medical imaging modalities. In an exemplary embodiment, acquiring the sequence of 2D IV images may include utilizing at least one of an intravascular ultrasound (IVUS) imaging modality and an intravascular optical coherence tomography (IVOCT) imaging modality.

[0008] In an exemplary embodiment, extracting the set of IV longitudinal images from the sequence of 2D IV images may include extracting each respective segment of a respective IV longitudinal image in the set of IV longitudinal images from a respective 2D IV image of the sequence of 2D IV images along a respective hypothetical line of a plurality of hypothetical lines. An exemplary respective hypothetical line may pass through a center of the respective 2D IV image at a respective angle from a lateral axis of the respective 2D IV image.

[0009] In an exemplary embodiment, estimating the 2D motion signal may include extracting variations of horizontal coordinates of the sequence of geometric mass centers and variations of lateral coordinates of the sequence of geometric mass centers.

[0010] Other exemplary systems, methods, features and advantages of the implementations will be, or will become, apparent to one of ordinary skill in the art upon examination of thefollowing figures and detailed description. It is intended that all such additional systems, methods, features and advantages be included within this description and this summary, be within the scope of the implementations, and be protected by the claims herein. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The drawing figures depict one or more implementations in accord with the present teachings, by way of example only, not by way of limitation. In the figures, like reference numerals refer to the same or similar elements.

[0012] FIG.1 shows a flowchart for method for three-dimensional (3D) imaging of coronary arteries, consistent with one or more exemplary embodiments of the present disclosure.

[0013] FIG.2 shows a schematic of a system for 3D imaging of coronary arteries, consistent with one or more exemplary embodiments of the present disclosure.

[0014] FIG. 3 shows a sequence of two-dimensional (2D) intravascular (IV) images of a coronary artery, consistent with one or more exemplary embodiments of the present disclosure.

[0015] FIG.4 shows a schematic of extracting a set of IV longitudinal images from a sequence of 2D IV images, consistent with one or more exemplary embodiments of the present disclosure.

[0016] FIG. 5 shows an IV longitudinal image of a coronary artery, consistent with one or more exemplary embodiments of the present disclosure.

[0017] FIG.6 shows a geometric mass center of a coronary artery marked on a 2D IV image of the coronary artery, consistent with one or more exemplary embodiments of the present disclosure.

[0018] FIG.7 shows diagrams of variations of a 2D motion signal, consistent with one or more exemplary embodiments of the present disclosure.

[0019] FIG.8 shows a schematic of two successive 2D IV images, consistent with one or more exemplary embodiments of the present disclosure.

[0020] FIG. 9A shows diagrams of variations of a sequence of lateral rotation angles, consistent with one or more exemplary embodiments of the present disclosure.

[0021] FIG.9B shows diagrams of variations of different sequences of rotation angles before and after filtering undesired frequency components, consistent with one or more exemplary embodiments of the present disclosure.

[0022] FIG.10A shows a schematic of horizontal displacement of a sequence of displaced IV images, consistent with one or more exemplary embodiments of the present disclosure.

[0023] FIG. 10B shows a schematic of lateral displacement of a sequence of displaced IV images, consistent with one or more exemplary embodiments of the present disclosure.

[0024] FIG.10C shows a schematic of a sequence of transformed IV frames, consistent with one or more exemplary embodiments of the present disclosure.

[0025] FIG.11 shows a schematic of a 3D image of a coronary artery, consistent with one or more exemplary embodiments of the present disclosure.

[0026] FIG.12 shows a high-level functional block diagram of a computer system, consistent with one or more exemplary embodiments of the present disclosure.

[0027] FIG. 13 shows an angiogram of a coronary artery, consistent with exemplary embodiments of the present disclosure.

[0028] FIG. 14 shows an IV longitudinal image of a coronary artery, consistent with exemplary embodiments of the present disclosure.

[0029] FIG.15 shows a 3D image of a coronary artery, consistent with one or more exemplary embodiments of the present disclosure. DESCRIPTION OF EMBODIMENTS

[0030] In the following detailed description, numerous specific details are set forth by way of examples in order to provide a thorough understanding of the relevant teachings. However, it should be apparent that the present teachings may be practiced without such details. In other instances, well known methods, procedures, components, and / or circuitry have been described at a relatively high-level, without detail, in order to avoid unnecessarily obscuring aspects of the present teachings.

[0031] The following detailed description is presented to enable a person skilled in the art to make and use the methods and devices disclosed in exemplary embodiments of the present disclosure. For purposes of explanation, specific nomenclature is set forth to provide a thorough understanding of the present disclosure. However, it will be apparent to one skilled in the art that these specific details are not required to practice the disclosed exemplary embodiments. Descriptions of specific exemplary embodiments are provided only as representative examples. Various modifications to the exemplary implementations will be readily apparent to one skilled in the art, and the general principles defined herein may be applied to other implementationsand applications without departing from the scope of the present disclosure. The present disclosure is not intended to be limited to the implementations shown, but is to be accorded the widest possible scope consistent with the principles and features disclosed herein.

[0032] Herein is disclosed an exemplary method and an exemplary system for three- dimensional (3D) imaging of coronary arteries. An exemplary method may be applied to a sequence of two-dimensional (2D) intravascular (IV) images of a coronary artery. Exemplary intravascular images may be obtained by conventional intravascular imaging modalities such as an intravascular ultrasound (IVUS) imaging system or an intravascular optical coherence tomography (IVOCT) imaging system. An exemplary imaging method may obtain a longitudinal image of the coronary artery from the sequence of IV images. Next, Lumen and media-adventitia borders of the coronary artery may be extracted from the longitudinal image by an exemplary method. Based on extracted borders, an exemplary method may estimate 2D movements of the geometric mass center of the coronary artery inside 2D planes of IV images. Afterwards, an exemplary 3D movement of each IV image with respect to a previous image in the sequence of IV images may be estimated according to estimated movements of the geometric mass center of the coronary artery. For this purpose, IV images may be displaced so that the geometric mass center may be positioned at the center of each image. As a result, 2D movements of IV images may be compensated. Therefore, an exemplary 3D movement of IV images may be estimated based on 3D angular displacement of each displaced IV image. For this purpose, an exemplary 3D angular displacement may be divided into three orthogonal elements of horizontal, lateral, and vertical angular displacements. An exemplary 3D angular displacement may be estimated by obtaining each of angular displacement elements.

[0033] An exemplary horizontal angular displacement (i.e, rotation angle of each displaced IV image with respect to a previous one in a same 2D plane of IV images) may be estimated as a phase difference of Fourier transforms of each two successive displaced images. To obtain lateral and vertical angular displacements, each displaced IV image may be rotated by different possible lateral and vertical rotation angles. An exemplary pair of lateral and vertical rotation angles that may result in a maximum similarity (in terms of cross-correlation) between a rotated image and a previous displaced IV image in the sequence of IV images may be considered as an estimated pair of lateral and vertical rotation angles of a corresponding IV image. Finally, each IV frame may be placed in a sequence of frames based on estimated 3D angular displacements and 2D motions to reconstruct a 3D image of the coronary artery.

[0034] FIG.1 shows a flowchart for method for three-dimensional (3D) imaging of coronary arteries, consistent with one or more exemplary embodiments of the present disclosure. An exemplary method 100 may include acquiring a sequence of two-dimensional (2D) intravascular (IV) images of a coronary artery (step 102), extracting a set of IV longitudinal images from the sequence of 2D IV images (step 104), detecting a lumen border of the coronary artery and a media-adventitia (MA) border of the coronary artery based on the set of IV longitudinal images (step 106), estimating a sequence of geometric mass centers of the coronary artery based on the lumen border and the MA border (step 108), estimating a 2D motion signal of the coronary artery from the sequence of geometric mass centers (step 110), estimating a respective rotation of a sequence of rotations for each respective 2D IV image of the sequence of 2D IV images with respect to a previous 2D IV image of the sequence of 2D IV images based on the 2D motion signal (step 112), generating a sequence of transformed IV frames from the sequence of 2D IV images based on the sequence of rotations and the 2D motion signal (step 114), and reconstructing a 3D image of the coronary artery from the sequence of transformed IV frames (step 116). An exemplary 3D image may be reconstructed based on an imaging speed of the one or more medical imaging modalities.

[0035] FIG.2 shows a schematic of a system for 3D imaging of coronary arteries, consistent with one or more exemplary embodiments of the present disclosure. An exemplary system 200 may include one or more medical imaging modalities 202 and a processor 204. In an exemplary embodiment, one or more medical imaging modalities 202 may include a catheter 206 that may be utilized for acquiring the sequence of 2D IV images of a coronary artery 208. In an exemplary embodiment, different steps of method 100 may be implemented by utilizing system 200. In an exemplary embodiment, one or more medical imaging modalities 202 may include an intravascular ultrasound (IVUS) imaging modality or an intravascular optical coherence tomography (IVOCT) imaging modality, or a combination thereof.

[0036] In further detail with respect to step 102, FIG.3 shows a sequence of 2D IV images of a coronary artery, consistent with one or more exemplary embodiments of the present disclosure. In an exemplary embodiment, catheter 206 may be inserted inside coronary artery 208 and may be pulled at a given speed to acquire a sequence 300 of 2D IV images of coronary artery 208 in step 102.

[0037] For further detail regarding step 104, FIG.4 shows a schematic 400 of extracting a set of IV longitudinal images from a sequence of 2D IV images, consistent with one or moreexemplary embodiments of the present disclosure. In an exemplary embodiment, extracting a set 402 of IV longitudinal images from sequence 300 of 2D IV images may include extracting each respective segment of a respective IV longitudinal image in set 402 of IV longitudinal images from a respective 2D IV image of sequence 300 of 2D IV images along a respective hypothetical line of a plurality of hypothetical lines. For example, a segment 404 of an IV longitudinal image 406 in set 402 may be extracted from a 2D IV image 408 of sequence 300 along a hypothetical line 410. As another example, a segment 412 of an IV longitudinal image 414 in set 402 may be extracted from 2D IV image 408 along a hypothetical line 416. In an exemplary embodiment, each respective hypothetical line may pass through a center of a respective 2D IV image at a respective angle from a horizontal axis ^ of the respective 2D IV image. For example, hypothetical line 410 may pass through a center 418 of 2D IV image 408 at a 0° angle from horizontal axis ^. In an exemplary embodiment, hypothetical line 416 may pass through center 418 at a 90° angle from horizontal axis ^.

[0038] For further detail regarding step 106, FIG.5 shows an IV longitudinal image 500 of a coronary artery, consistent with one or more exemplary embodiments of the present disclosure. In an exemplary embodiment, a lumen border 502 and an MA border 504 of a coronary artery may be extracted from IV longitudinal image 500 in step 106 utilizing different border extraction methods.

[0039] For further detail with respect to step 108, FIG.6 shows a geometric mass center of a coronary artery marked on a 2D IV image of the coronary artery, consistent with one or more exemplary embodiments of the present disclosure. In an exemplary embodiment, estimating the sequence of geometric mass centers in step 108 may include fitting a respective inner ellipse of a plurality of inner ellipses to points of the lumen border in segments of each respective IV longitudinal image in the set of IV longitudinal images. For example, referring to FIGs.4, 5, and 6, an inner ellipse 602 may be fitted to points 604A, 604B, 604C, and 604D that may be extracted from a lumen border (similar to lumen border 502) in segments (similar to segments 404 and 412) of corresponding IV longitudinal images (similar to IV longitudinal images 406 and 414) in the set of IV longitudinal images (similar to set 402). In an exemplary embodiment, at least four different points may be needed to fit inner ellipse 602 to the lumen border. Therefore, in an exemplary embodiment, set 402 may have at least four IV longitudinal images that may be extracted along at least four hypothetical lines along four different from horizontal axis ^, so that four different segments corresponding to each 2D IV image may be obtained.

[0040] In an exemplary embodiment, estimating the sequence of geometric mass centers in step 108 may further include fitting a respective outer ellipse of a plurality of outer ellipses to points of the MA border in segments of each respective IV longitudinal image in the set of IV longitudinal images. For example, an outer ellipse 606 may be fitted to points 608A, 608B, 608C, and 608D that may be extracted from an MA border (similar to MA border 504) in segments (similar to segments 404 and 412) of corresponding IV longitudinal images (similar to IV longitudinal images 406 and 414) in the set of IV longitudinal images (similar to set 402). Similar to fitting inner ellipse 602 to the lumen border discussed above, in an exemplary embodiment, at least four different points may be needed to fit outer ellipse 606 to the MA border that may be extracted from four different segments of four corresponding IV longitudinal images.

[0041] In an exemplary embodiment, estimating the sequence of geometric mass centers in step 108 may further include estimating a geometric mass center ^^of the sequence of geometric mass centers according to an operation defined by the following: Equation (1)where ^̅ is a horizontal coordinate of geometric mass center ^^in a direction of horizontal axis ^, ^ is a lateral coordinate of geometric mass center ^^in a direction of a lateral axis ^ of a respective 2D IV image (for example, 2D IV image 408), ^ is a horizontal coordinate of a respective point in 2D IV image 408, ^ is a lateral coordinate of a respective point in 2D IV image 408, ^^^ is an area outside inner ellipse 602, ^^^is an area inside outer ellipse 606, and ^ is a number of points inside areas ^^^ and ^^^. In an exemplary embodiment, horizontalcoordinates ^ and ^̅ may be defined at a direction of horizontal axis ^ . In an exemplaryembodiment, lateral coordinates ^ and ^ may be defined at a direction of lateral axis ^.

[0042] In further detail with respect to step 110, FIG.7 shows diagrams of variations of a 2D motion signal, consistent with one or more exemplary embodiments of the present disclosure. In an exemplary embodiment, estimating the 2D motion signal may include extracting variations of horizontal coordinates of the sequence of geometric mass centers and variations of lateral coordinates of the sequence of geometric mass centers. For example, a diagram 702 shows variations of horizontal coordinate ^̅ of geometric mass center ^^with respect to frames of sequence 300 of 2D IV images. Also, an exemplary diagram 704 shows variations of lateralcoordinate ^ of geometric mass center ^^with respect to frames of sequence 300 of 2D IV images.

[0043] For further detail regarding step 112, FIG.8 shows a schematic of two successive 2D IV images, consistent with one or more exemplary embodiments of the present disclosure. In an exemplary embodiment, estimating a respective rotation of the sequence of rotations for each respective 2D IV image of the sequence of 2D IV images respect to the previous 2D IV image in step 112 may include calculating a horizontal rotation angle ^^of a sequence ofhorizontal rotation angles for an (^ + 1)^^ 2D IV image 802 of sequence of 2D IV images 300with respect to an ^^^2D IV image 804 of sequence of 2D IV images 300 about a vertical axis^ that may be perpendicular to ^^^ 2D IV image 804, where 1 ≤ ^ < ^ and ^ is a number of2D IV images in sequence of 2D IV images 300, according to an operation defined by the following: Equation (2)where ^^^^^^is a Fourier transform of a polar representation ^^^^^ of ^^^2D IV image 804,is a Fourier transform of a polar representation ^(^ + 1)^^2D IV image 802, and ^(∙) is asignal phase. In an exemplary embodiment, polar representation ^^^^^may be given by the following:Equation (3) where ^̅^is a horizontal coordinate of an ^^^geometric mass center 806 of the sequence ofgeometric mass centers, ^^(^, ^) is a value of ^^^ 2D IV image 804 at a distance ^ from ^^^geometric mass center 806 and an angle ^ from horizontal axis ^ of ^^^2D IV image 804. Exemplary horizontal coordinates may be defined at an exemplary direction of horizontal axis ^.

[0044] In an exemplary embodiment, estimating a respective rotation of the sequence of rotations for each respective 2D IV image of the sequence of 2D IV images respect to theprevious 2D IV image in step 112 may further include obtaining a plurality of (^ + 1)^^ rotated2D IV images by rotating (^ + 1)^^ 2D IV image 802 according to a rotation matrix definedby the following: Equation (4)where ^ is a rotation matrix about horizontal axis ^, ^^ ∈ [−^ , ^ ^^^ is a lateral rotation anglecandidate about horizontal axis ^, ^ is a rotation matrix about lateral axis ^, ^^ ∈ [−^ , ^] is^ ^^ ^ a vertical rotation angle candidate about lateral axis ^, and ^ is a rotation matrix about vertical^axis ^. In an exemplary embodiment, a “rotation matrix” may refer to a transformation matrix cos ^that is used to perform a rotation in Euclidean space and may be defined as ^ sin ^where ^ is a rotation angle.

[0045] In an exemplary embodiment, estimating a respective rotation of the sequence of rotations for each respective 2D IV image of the sequence of 2D IV images respect to the previous 2D IV image in step 112 may further include obtaining a plurality of mapped images. An exemplary mapped image may be obtained by mapping rotated 2D IV image of the plurality ^^ ^^ ( ) of ^ + 1 rotated 2D IV images to a 2D plane ^^ of ^ 2D IV image 804.

[0046] In an exemplary embodiment, estimating a respective rotation of the sequence of rotations for each respective 2D IV image of the sequence of 2D IV images respect to the previous 2D IV image in step 112 may further include calculating a lateral rotation angle ^^of a sequence of lateral rotation angles about horizontal axis ^ and a vertical rotation angle ^^^^ ( ) of a sequence of vertical rotation angles about lateral axis ^ for ^ + 1 2D IV image 802^^with respect to the ^ 2D IV image 804 according to an operation defined by the following: ^^ , ^ ^ = arg Equation (5)^ ^where ^^^^ , ^^ ^ is a peak value of a cross-correlation function between a respective mapped^ ^^^image of the plurality of mapped images and ^ 2D IV image 804.

[0047] In an exemplary embodiment, method 100 may further include filtering frequency samples between about 0.3 Hz and about 0.6 Hz and frequency samples between about 0.75 Hz and about 1.3 Hz of each of the sequence of lateral rotation angles, the sequence of vertical rotation angles, and the sequence of horizontal rotation angles prior to generating the sequence of transformed IV frames in step 114.

[0048] FIG. 9A shows diagrams of variations of a sequence of lateral rotation angles, consistent with one or more exemplary embodiments of the present disclosure. An exemplary diagram 902 shows variations of the sequence of lateral rotation angles with respect to frames of sequence 300 of 2D IV images. An exemplary diagram 904 shows variations of the sequence of lateral rotation angles in the frequency domain. An exemplary frequency range 906 of about0.3 Hz to about 0.6 Hz and an exemplary frequency range 908 of about 0.75 Hz and about 1.3 Hz of diagram 904 may be filtered to remove undesired breathing and cardiac effects on diagram 904. In an exemplary embodiment, different filters may be applied to the sequences of rotation angles to remove undesired interferences. For example, notch filters may be applied to frequency ranges 906 and 908, or a lowpass Butterworth filter with a cut-off frequency of about 0.16 Hz may applied to the sequences of rotation angles.

[0049] FIG.9B shows diagrams of variations of different sequences of rotation angles before and after filtering undesired frequency components, consistent with one or more exemplary embodiments of the present disclosure. An exemplary diagram 910A shows variations of the sequence of horizontal rotation angles before filtering frequency ranges 906 and 908. An exemplary diagram 910B shows variations of the sequence of horizontal rotation angles after filtering frequency ranges 906 and 908. An exemplary diagram 912A shows variations of the sequence of lateral rotation angles before filtering frequency ranges 906 and 908. An exemplary diagram 912B shows variations of the sequence of lateral rotation angles after filtering frequency ranges 906 and 908. An exemplary diagram 914A shows variations of the sequence of vertical rotation angles before filtering frequency ranges 906 and 908. An exemplary diagram 914B shows variations of the sequence of vertical rotation angles after filtering frequency ranges 906 and 908. Comparing diagrams 910A, 912A, and 914A with corresponding diagrams 910B, 912B, and 914B shows that filtering undesired breathing and cardiac effects may eliminate sharp variations of rotation angles that may be caused by fast movements of coronary artery 208 due to breathing or heartbeat, leaving geometrical variations of coronary artery 208 as a main cause of variations of different rotation angles.

[0050] For further detail regarding step 114, FIG.10A shows a schematic 1000A of horizontal displacement of a sequence of displaced IV images, consistent with one or more exemplary embodiments of the present disclosure. FIG. 10B shows a schematic 1000B of lateral displacement of a sequence of displaced IV images, consistent with one or more exemplary embodiments of the present disclosure. In an exemplary embodiment, generating the sequence of transformed IV frames in step 114 may include obtaining a sequence of displaced IV images 1002 by displacing each of sequence of 2D IV images 300 according to the sequence of geometric mass centers. For example, a 2D IV image 1004 of sequence of 2D IV images 300may be displaced by ^^̅ − ^^̅ in horizontal direction ^ and by ^^ − ^^ in lateral direction ^ toobtain a displaced 2D IV image 1006 of sequence of 2D IV images 300 where ^^̅ and ^^arerespectively horizontal and vertical coordinates of a geometric mass center ^^^of 2D IV image 1004, and ^^̅ and ^^are respectively horizontal and vertical coordinates of a geometric mass center ^^^of 2D IV image 1006.

[0051] In further detail regarding step 114, FIG.10C shows a schematic 1000C of a sequence of transformed IV frames, consistent with one or more exemplary embodiments of the present disclosure. Referring to FIGs.8, 10A, 10B, and 10C, in an exemplary embodiment, step 114 may further include obtaining a sequence 1008 of transformed IV frames by rotating each of the sequence of displaced IV images according to a respective lateral rotation angle of the sequence of lateral rotation angles about horizontal axis ^, a respective vertical rotation angle of the sequence of vertical rotation angles about lateral axis ^, and a respective horizontal rotation angle of the sequence of horizontal rotation angles about vertical axis ^. For example, a transformed IV frame 1010 may be obtained by rotating displaced 2D IV image 1004 by lateral rotation angle ^^about horizontal axis ^, vertical rotation angle ^^about lateral axis ^, and horizontal rotation angle ^^about vertical axis ^.

[0052] For further detail with respect to step 116, FIG. 11 shows a schematic 1100 of a 3D image of a coronary artery, consistent with one or more exemplary embodiments of the present disclosure. Referring to FIGs.2, 10C, and 11, in an exemplary embodiment, reconstructing a 3D image 11002 of coronary artery 208 from sequence 1008 of transformed IV frames in step 116 may include placing each transformed IV frame of sequence 1008 of transformed IV frames at a distance ^ from a previous transformed IV frame of sequence 1008 of transformedIV frames. In an exemplary embodiment, distance ^ may be determined according to anoperation defined by the following: Equation (6)where ^^is a pullback speed of catheter 206 and ^^is an imaging speed of one or more medical imaging modalities 202.

[0053] FIG. 12 shows an example computer system 1200 in which an embodiment of the present invention, or portions thereof, may be implemented as computer-readable code, consistent with exemplary embodiments of the present disclosure. For example, method 100 may be implemented in computer system 1200 using hardware, software, firmware, tangible computer readable media having instructions stored thereon, or a combination thereof and may be implemented in one or more computer systems or other processing systems. Hardware,software, or any combination of such may embody any of the modules and components in FIGs.1-11. In particular, in an exemplary embodiment, computer system 1200 may embody processor 204 of FIG.2.

[0054] If programmable logic is used, such logic may execute on a commercially available processing platform or a special purpose device. One ordinary skill in the art may appreciate that an embodiment of the disclosed subject matter can be practiced with various computer system configurations, including multi-core multiprocessor systems, minicomputers, mainframe computers, computers linked or clustered with distributed functions, as well as pervasive or miniature computers that may be embedded into virtually any device.

[0055] For instance, a computing device having at least one processor device and a memory may be used to implement the above-described embodiments. A processor device may be a single processor, a plurality of processors, or combinations thereof. Processor devices may have one or more processor “cores.”

[0056] An embodiment of the invention is described in terms of this example computer system 1200. After reading this description, it will become apparent to a person skilled in the relevant art how to implement the invention using other computer systems and / or computer architectures. Although operations may be described as a sequential process, some of the operations may in fact be performed in parallel, concurrently, and / or in a distributed environment, and with program code stored locally or remotely for access by single or multi- processor machines. In addition, in some embodiments the order of operations may be rearranged without departing from the spirit of the disclosed subject matter.

[0057] Processor device 1204 may be a special purpose (e.g., a graphical processing unit) or a general-purpose processor device. As will be appreciated by persons skilled in the relevant art, processor device 1204 may also be a single processor in a multi-core / multiprocessor system, such system operating alone, or in a cluster of computing devices operating in a cluster or server farm. Processor device 1204 may be connected to a communication infrastructure 1206, for example, a bus, message queue, network, or multi-core message-passing scheme.

[0058] In an exemplary embodiment, computer system 1200 may include a display interface 1202, for example a video connector, to transfer data to a display unit 1230, for example, a monitor. Computer system 1200 may also include a main memory 1208, for example, random access memory (RAM), and may also include a secondary memory 1210. Secondary memory 1210 may include, for example, a hard disk drive 1212, and a removable storage drive 1214.Removable storage drive 1214 may include a floppy disk drive, a magnetic tape drive, an optical disk drive, a flash memory, or the like. Removable storage drive 1214 may read from and / or write to a removable storage unit 1218 in a well-known manner. Removable storage unit 1218 may include a floppy disk, a magnetic tape, an optical disk, etc., which may be read by and written to by removable storage drive 1214. As will be appreciated by persons skilled in the relevant art, removable storage unit 1218 may include a computer usable storage medium having stored therein computer software and / or data.

[0059] In alternative implementations, secondary memory 1210 may include other similar means for allowing computer programs or other instructions to be loaded into computer system 1200. Such means may include, for example, a removable storage unit 1222 and an interface 1220. Examples of such means may include a program cartridge and cartridge interface (such as that found in video game devices), a removable memory chip (such as an EPROM, or PROM) and associated socket, and other removable storage units 1222 and interfaces 1220 which allow software and data to be transferred from removable storage unit 1222 to computer system 1200.

[0060] Computer system 1200 may also include a communications interface 1224. Communications interface 1224 allows software and data to be transferred between computer system 1200 and external devices. Communications interface 1224 may include a modem, a network interface (such as an Ethernet card), a communications port, a PCMCIA slot and card, or the like. Software and data transferred via communications interface 1224 may be in the form of signals, which may be electronic, electromagnetic, optical, or other signals capable of being received by communications interface 1224. These signals may be provided to communications interface 1224 via a communications path 1226. Communications path 1226 carries signals and may be implemented using wire or cable, fiber optics, a phone line, a cellular phone link, an RF link or other communications channels.

[0061] In this document, the terms “computer program medium” and “computer usable medium” are used to generally refer to media such as removable storage unit 1218, removable storage unit 1222, and a hard disk installed in hard disk drive 1212. Computer program medium and computer usable medium may also refer to memories, such as main memory 1208 and secondary memory 1210, which may be memory semiconductors (e.g. DRAMs, etc.).

[0062] Computer programs (also called computer control logic) are stored in main memory 1208 and / or secondary memory 1210. Computer programs may also be received viacommunications interface 1224. Such computer programs, when executed, enable computer system 1200 to implement different embodiments of the present disclosure as discussed herein. In particular, the computer programs, when executed, enable processor device 1204 to implement the processes of the present disclosure, such as the operations in method 100 illustrated by flowchart 100 of FIG.1 discussed above. Accordingly, such computer programs represent controllers of computer system 1200. Where an exemplary embodiment of method 100 is implemented using software, the software may be stored in a computer program product and loaded into computer system 1200 using removable storage drive 1214, interface 1220, and hard disk drive 1212, or communications interface 1224.

[0063] Embodiments of the present disclosure also may be directed to computer program products including software stored on any computer useable medium. Such software, when executed in one or more data processing device, causes a data processing device to operate as described herein. An embodiment of the present disclosure may employ any computer useable or readable medium. Examples of computer useable mediums include, but are not limited to, primary storage devices (e.g., any type of random access memory), secondary storage devices (e.g., hard drives, floppy disks, CD ROMS, ZIP disks, tapes, magnetic storage devices, and optical storage devices, MEMS, nanotechnological storage device, etc.).

[0064] The embodiments have been described above with the aid of functional building blocks illustrating the implementation of specified functions and relationships thereof. The boundaries of these functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternate boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed. EXAMPLE

[0065] In this example, results of an exemplary embodiment of method 100 is demonstrated. FIG. 13 shows an angiogram 1300 of a coronary artery 1302, consistent with exemplary embodiments of the present disclosure. FIG.14 shows an IV longitudinal image of a coronary artery, consistent with exemplary embodiments of the present disclosure. An exemplary IV longitudinal image 1400 of coronary artery 1302 is analogous to IV longitudinal image 406 of FIG.4 and is obtained by implementing step 104 of method 100. FIG.15 shows a 3D image of a coronary artery, consistent with one or more exemplary embodiments of the present disclosure. An exemplary 3D image 1500 of coronary artery 1302 is obtained by applying anexemplary embodiment of method 100 to a sequence of about 1800 IVUS frames (analogous to sequence 300 of 2D IV images of FIG.3). As shown in FIG.15, 3D image 1500 properly illustrates shape, and particularly, curvature of coronary artery 1302.

[0066] While the foregoing has described what are considered to be the best mode and / or other examples, it is understood that various modifications may be made therein and that the subject matter disclosed herein may be implemented in various forms and examples, and that the teachings may be applied in numerous applications, only some of which have been described herein. It is intended by the following claims to claim any and all applications, modifications, and variations that fall within the true scope of the present teachings.

[0067] Unless otherwise stated, all measurements, values, ratings, positions, magnitudes, sizes, and other specifications that are set forth in this specification, including in the claims that follow, are approximate, not exact. They are intended to have a reasonable range that is consistent with the functions to which they relate and with what is customary in the art to which they pertain.

[0068] The scope of protection is limited solely by the claims that now follow. That scope is intended and should be interpreted to be as broad as is consistent with the ordinary meaning of the language that is used in the claims when interpreted in light of this specification and the prosecution history that follows and to encompass all structural and functional equivalents.

[0069] Except as stated immediately above, nothing that has been stated or illustrated is intended or should be interpreted to cause a dedication of any component, step, feature, object, benefit, advantage, or equivalent to the public, regardless of whether it is or is not recited in the claims.

[0070] It will be understood that the terms and expressions used herein have the ordinary meaning as is accorded to such terms and expressions with respect to their corresponding respective areas of inquiry and study except where specific meanings have otherwise been set forth herein. Relational terms such as first and second and the like may be used solely to distinguish one entity or action from another without necessarily requiring or implying any actual such relationship or order between such entities or actions. The terms “comprises,” “comprising,” or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by “a” or “an” does not,without further constraints, preclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0071] The Abstract of the Disclosure is provided to allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. In addition, in the foregoing Detailed Description, it can be seen that various features are grouped together in various implementations. This is for purposes of streamlining the disclosure, and is not to be interpreted as reflecting an intention that the claimed implementations require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed implementation. Thus, the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separately claimed subject matter.

[0072] While various implementations have been described, the description is intended to be exemplary, rather than limiting and it will be apparent to those of ordinary skill in the art that many more implementations and implementations are possible that are within the scope of the implementations. Although many possible combinations of features are shown in the accompanying figures and discussed in this detailed description, many other combinations of the disclosed features are possible. Any feature of any implementation may be used in combination with or substituted for any other feature or element in any other implementation unless specifically restricted. Therefore, it will be understood that any of the features shown and / or discussed in the present disclosure may be implemented together in any suitable combination. Accordingly, the implementations are not to be restricted except in light of the attached claims and their equivalents. Also, various modifications and changes may be made within the scope of the attached claims.

Claims

What is claimed is:

1. A method for three-dimensional (3D) imaging of coronary arteries, the method comprising: acquiring, utilizing one or more medical imaging modalities, a sequence of two- dimensional (2D) intravascular (IV) images of a coronary artery; extracting, utilizing one or more processors, a set of IV longitudinal images from the sequence of 2D IV images; detecting, utilizing the one or more processors, a lumen border of the coronary artery and a media-adventitia (MA) border of the coronary artery based on the set of IV longitudinal images; estimating, utilizing the one or more processors, a sequence of geometric mass centers of the coronary artery based on the lumen border and the MA border; estimating, utilizing the one or more processors, a 2D motion signal of the coronary artery from the sequence of geometric mass centers; estimating, utilizing the one or more processors, a respective rotation of a sequence of rotations for each respective 2D IV image of the sequence of 2D IV images with respect to a previous 2D IV image of the sequence of 2D IV images based on the 2D motion signal; generating, utilizing the one or more processors, a sequence of transformed IV frames from the sequence of 2D IV images based on the sequence of rotations and the 2D motion signal; and reconstructing, utilizing the one or more processors, a 3D image of the coronary artery from the sequence of transformed IV frames based on an imaging speed of the one or more medical imaging modalities.

2. The method of claim 1, wherein acquiring the sequence of 2D IV images comprises utilizing at least one of an intravascular ultrasound (IVUS) imaging modality and an intravascular optical coherence tomography (IVOCT) imaging modality.

3. The method of claim 1, wherein extracting the set of IV longitudinal images from the sequence of 2D IV images comprises extracting each respective segment of a respective IV longitudinal image in the set of IV longitudinal images from a respective 2D IV image of the sequence of 2D IV images along a respective hypothetical line of a plurality of hypothetical lines, the respective hypothetical line passing through a center of the respective 2D IV image at a respective angle from a lateral axis of the respective 2D IV image.

4. The method of claim 3, wherein estimating the sequence of geometric mass centers comprises: fitting a respective inner ellipse of a plurality of inner ellipses to points of the lumen border in segments of each respective IV longitudinal image in the set of IV longitudinal images; fitting a respective outer ellipse of a plurality of outer ellipses to points of the MA border in segments of each respective IV longitudinal image in the set of IV longitudinal images; and estimating a geometric mass center ^^of the sequence of geometric mass centers according to an operation defined by the following:where: ^̅ is a horizontal coordinate of the geometric mass center, ^ is a lateral coordinate of the geometric mass center, ^ is a horizontal coordinate of a respective point in a respective 2D IV image of the sequence of 2D IV images, ^ is a lateral coordinate of a respective point in a respective 2D IV image of the sequence of 2D IV images, ^^^ is an area outside the respective inner ellipse, ^^^is an area inside the respective outer ellipse, and ^ is a number of points inside the areas ^^^ and ^^^.

5. The method of claim 4, wherein estimating the 2D motion signal comprises extracting variations of horizontal coordinates of the sequence of geometric mass centers and variations of lateral coordinates of the sequence of geometric mass centers.

6. The method of claim 5, wherein estimating a respective rotation of the sequence of rotations for each respective 2D IV image of the sequence of 2D IV images respect to the previous 2D IV image comprises: calculating a horizontal rotation angle ^^of a sequence of horizontal rotation angles for an(^ + 1)^^ 2D IV image of the sequence of 2D IV images with respect to an ^^^ 2D IV image of thesequence of 2D IV images about a vertical axis ^ perpendicular to the ^^^2D IV image, where1 ≤ ^ < ^ and ^ is a number of 2D IV images in the sequence of 2D IV images, according to anoperation defined by the following:where: ^^^^^^is a Fourier transform of a polar representation ^^^^^of the ^^^2D IV image where the polar representation ^^^^^is given by the following:where: ^̅^is a horizontal coordinate of an ^^^geometric mass center of the sequence of geometric mass centers, ^^is a lateral coordinate of the ^^^geometric mass center, and ^^(^, ^) is a value of the ^^^ 2D IV image at a distance ^ from the ^^^geometric mass center and an angle ^ from a horizontal axis ^ of the ^^^2D IV image, the horizontal axis ^ associated with the horizontal coordinates, ^^^^^^^^is a Fourier transform of a polar representation ^^the (^ + 1) ^ 2D IV image,and ^(∙) is a signal phase; obtaining a plurality of (^ + 1)^^ rotated 2D IV images by rotating the (^ + 1)^^ 2D IVimage according to a rotation matrix defined by the following: ℜ= ^^(^^^) × ^^^^^^^ × ^^(−^^)where: ^^is a rotation matrix about the horizontal axis ^, ^^^ ∈ [−^ ^ ^ , ^] is a lateral rotation angle candidate about the horizontal axis ^, ^^is a rotation matrix about a lateral axis ^ associated with the lateral coordinates, ^^is a vertical rotation angle candidate about the lateral axis ^, ^^is a rotation matrix about the vertical axis ^; obtaining a plurality of mapped images by mapping each of the plurality of (^ + 1)^^rotated 2D IV images to a 2D plane of the ^^^2D IV image; andcalculating a lateral rotation angle ^^of a sequence of lateral rotation angles about the horizontal axis ^ and a vertical rotation angle ^^of a sequence of vertical rotation angles aboutthe lateral axis ^ for the (^ + 1)^^ 2D IV image with respect to the ^^^ 2D IV image according toan operation defined by the following:a peak value of a cross-correlation function between a respectivemapped image of the plurality of mapped images and the ^^^2D IV image.

7. The method of claim 6, wherein generating the sequence of transformed IV frames comprises: obtaining a sequence of displaced IV images by displacing each of the sequence of 2D IV images according to the sequence of geometric mass centers; and obtaining the sequence of transformed IV frames by rotating each of the sequence of displaced IV images according to: a respective lateral rotation angle of the sequence of lateral rotation angles about the horizontal axis ^; a respective vertical rotation angle of the sequence of vertical rotation angles about the lateral axis ^; and a respective horizontal rotation angle of the sequence of horizontal rotation angles about the vertical axis ^.

8. The method of claim 7, wherein reconstructing the 3D image comprises placing each transformed IV frame of the sequence of transformed IV frames at a distance ^ from a previous transformed IV frame of the sequence of transformed IV frames, the distance ^ determined according to an operation defined by the following:where ^^is a pullback speed of a catheter of the one or more medical imaging modalities and ^^is an imaging speed of the one or more medical imaging modalities.

9. The method of claim 7, further comprising:filtering, utilizing the one or more processors, frequency samples between 0.3 Hz and 0.6 Hz and frequency samples between 0.75 Hz and 1.3 Hz of each of the sequence of lateral rotation angles, the sequence of vertical rotation angles, and the sequence of horizontal rotation angles prior to generating the sequence of transformed IV frames.

10. A system for three-dimensional (3D) imaging of coronary arteries, the system comprising: one or more medical imaging modalities configured to acquire a sequence of two- dimensional (2D) intravascular (IV) images of a coronary artery; a memory having processor-readable instructions stored therein; and a processor configured to access the memory and execute the processor-readable instructions, which, when executed by the processor configures the processor to perform a method, the method comprising: extracting a set of IV longitudinal images from the sequence of 2D IV images; detecting a lumen border of the coronary artery and a media-adventitia (MA) border of the coronary artery based on the set of IV longitudinal images; estimating a sequence of geometric mass centers of the coronary artery based on the lumen border and the MA border; estimating a 2D motion signal of the coronary artery from the sequence of geometric mass centers; estimating a respective rotation of a sequence of rotations for each respective 2D IV image of the sequence of 2D IV images with respect to a previous 2D IV image of the sequence of 2D IV images based on the 2D motion signal; generating a sequence of transformed IV frames from the sequence of 2D IV images based on the sequence of rotations and the 2D motion signal; and reconstructing a 3D image of the coronary artery from the sequence of transformed IV frames based on an imaging speed of the one or more medical imaging modalities.

11. The system of claim 10, wherein the one or more medical imaging modalities comprises at least one of an intravascular ultrasound (IVUS) imaging modality and an intravascular optical coherence tomography (IVOCT) imaging modality.

12. The system of claim 10, wherein extracting the set of IV longitudinal images from the sequence of 2D IV images comprises extracting each respective segment of a respective IV longitudinal image in the set of IV longitudinal images from a respective 2D IV image of the sequence of 2D IV images along a respective hypothetical line of a plurality of hypothetical lines, the respective hypothetical line passing through a center of the respective 2D IV image at a respective angle from a lateral axis of the respective 2D IV image.

13. The system of claim 12, wherein estimating the sequence of geometric mass centers comprises: fitting a respective inner ellipse of a plurality of inner ellipses to points of the lumen border in segments of each respective IV longitudinal image in the set of IV longitudinal images; fitting a respective outer ellipse of a plurality of outer ellipses to points of the MA border in segments of each respective IV longitudinal image in the set of IV longitudinal images; and estimating a geometric mass center ^^of the sequence of geometric mass centers according to an operation defined by the following:where: ^̅ is a horizontal coordinate of the geometric mass center, ^ is a lateral coordinate of the geometric mass center, ^ is a horizontal coordinate of a respective point in a respective 2D IV image of the sequence of 2D IV images, ^ is a lateral coordinate of a respective point in a respective 2D IV image of the sequence of 2D IV images, ^^^ is an area outside the respective inner ellipse, ^^^is an area inside the respective outer ellipse, and ^ is a number of points inside the areas ^^^ and ^^^.

14. The system of claim 13, wherein estimating the 2D motion signal comprises extracting variations of horizontal coordinates of the sequence of geometric mass centers and variations of lateral coordinates of the sequence of geometric mass centers.

15. The method of claim 14, wherein estimating a respective rotation of the sequence of rotations for each respective 2D IV image of the sequence of 2D IV images respect to the previous 2D IV image comprises: calculating a horizontal rotation angle ^^of a sequence of horizontal rotation angles for an(^ + 1)^^ 2D IV image of the sequence of 2D IV images with respect to an ^^^ 2D IV image of thesequence of 2D IV images about a vertical axis ^ perpendicular to the ^^^2D IV image, where1 ≤ ^ < ^ and ^ is a number of 2D IV images in the sequence of 2D IV images, according to anoperation defined by the following:where: ^^^^^^is a Fourier transform of a polar representation ^^^^^of the ^^^2D IV image where the polar representation ^^^^^is given by the following:where: where: ^̅^is a horizontal coordinate of an ^^^geometric mass center of the sequence of geometric mass centers, ^^is a lateral coordinate of the ^^^geometric mass center, and ^^(^, ^) is a value of the ^^^ 2D IV image at a distance ^ from the ^^^geometric mass center and an angle ^ from a horizontal axis ^ of the ^^^2D IV image, the horizontal axis ^ associated with the horizontal coordinates, ^^^^^^^^^^is a Fourier transform of a polar representation ^^^^^ the (^ + 1)^^ 2D IV image,and ^(∙) is a signal phase; obtaining a plurality of (^ + 1)^^ rotated 2D IV images by rotating the (^ + 1)^^ 2D IVimage according to a rotation matrix defined by the following:where:^^is a rotation matrix about the horizontal axis ^, ^^^ ∈is a lateral rotation angle candidate about the horizontal axis ^, ^^is a rotation matrix about a lateral axis ^ associated with the lateral coordinates, ^^^is a vertical rotation angle candidate about the lateral axis ^, and ^^is a rotation matrix about the vertical axis ^; obtaining a plurality of mapped images by mapping each of the plurality of (^ + 1)^^rotated 2D IV images to a 2D plane of the ^^^2D IV image; and calculating a lateral rotation angle ^^of a sequence of lateral rotation angles about the horizontal axis ^ and a vertical rotation angle ^^of a sequence of vertical rotation angles aboutthe lateral axis ^ for the (^ + 1)^^ 2D IV image with respect to the ^^^ 2D IV image according toan operation defined by the following:where ^^^^^, ^^^^ is a peak value of a cross-correlation function between a respectivemapped image of the plurality of mapped images and the ^^^2D IV image.

16. The system of claim 15, wherein generating the sequence of transformed IV frames comprises: obtaining a sequence of displaced IV images by displacing each of the sequence of 2D IV images according to the sequence of geometric mass centers; and obtaining the sequence of transformed IV frames by rotating each of the sequence of displaced IV images according to: a respective lateral rotation angle of the sequence of lateral rotation angles about the horizontal axis ^; a respective vertical rotation angle of the sequence of vertical rotation angles about the lateral axis ^; and a respective horizontal rotation angle of the sequence of horizontal rotation angles about the vertical axis ^.

17. The system of claim 16, wherein reconstructing the 3D image comprises placing each transformed IV frame of the sequence of transformed IV frames at a distance ^ from a previoustransformed IV frame of the sequence of transformed IV frames, the distance ^ determined according to an operation defined by the following:where ^^is a pullback speed of a catheter of the one or more medical imaging modalities and ^^is an imaging speed of the one or more medical imaging modalities.

18. The system of claim 16, wherein the method further comprises filtering frequency samples between 0.3 Hz and 0.6 Hz and frequency samples between 0.75 Hz and 1.3 Hz of each of the sequence of lateral rotation angles, the sequence of vertical rotation angles, and the sequence of horizontal rotation angles prior to generating the sequence of transformed IV frames.

Images