Lesion determination method and device

Abstract

An electronic device according to one embodiment can acquire a first trend line relating to blood vessels from a medical image, determine lesion candidates among the blood vessels based on the first trend line, acquire a second trend line based on a reference point selected from around the lesion candidate, and determine a lesion site among the lesion candidates based on the acquired second trend line.

Description

[Technical Field]

[0001] Below, techniques for determining lesions are provided. [Background technology]

[0002] Interventional procedures, such as inserting stents using catheters, are widely used to treat cardiovascular, cerebrovascular, and peripheral blood vessels. Before the procedure, the severity of the patient's lesion is evaluated using images from angiography. The treatment plan may change depending on the characteristics of the atherosclerotic plaque identified through angiography. In particular, if a calcified lesion is present, its rupture can lead to myocardial infarction by sending calcified fragments blocking the ends of the branches. Furthermore, when multiple lesions in the coronary arteries, including many calcified lesions, are present based on the SYNTAX score, surgical treatment may be more favorable for the prognosis. In this regard, there is a need for technology that can detect calcified lesions using X-ray angiography images instead of computer tomography (CT).

[0003] The above-mentioned background art was possessed or acquired by the inventors in the process of deriving the contents of the disclosure of this application, and is not necessarily publicly known art that was publicly disclosed prior to the filing of this application. Summary of the Invention [Problem to be solved by the invention]

[0004] The electronic device according to one embodiment is configured to search for multiple lesions in a blood vessel to be analyzed in a blood vessel image.

[0005] In one embodiment, the electronic device searches for lesion candidates and determines which lesions are clinically significant.

[0006] However, the technical issues are not limited to those mentioned above, and further technical issues may exist. [Means for solving the problem]

[0007] In one embodiment, a method for determining a lesion performed by a processor includes the steps of obtaining a first trend line relating to the diameter of a vessel from a medical image, determining a lesion candidate from the vessel based on the first trend line, obtaining a second trend line based on reference points selected from around the lesion candidate, and determining a lesion site from the lesion candidate based on the obtained second trend line.

[0008] The step of obtaining the first trend line includes a step of calculating a diameter within the vascular region to be analyzed in the medical image for each position along the center line based on a line perpendicular to the center line of the vascular region, and a step of obtaining the first trend line based on the calculated diameter.

[0009] The step of obtaining the first trend line may include the steps of: dividing a vascular region to be analyzed in the medical image into one or more vascular segments; calculating a regression line for the one or more vascular segments based on a regression analysis using a prior slope; excluding outliers selected based on the calculated regression line from diameters at positions along a centerline within the vascular segment; and calculating a regression line based on the diameters from which the outliers have been excluded.

[0010] The step of eliminating the outliers includes a step of determining, as the outliers, diameter values ​​at positions along the centerline within the blood vessel segment that exceed a range determined based on the initial regression line.

[0011] The step of obtaining the first trend line can include the step of repeatedly removing the outliers and calculating the regression line until a ratio of diameters determined to be outliers among diameters at positions along the centerline within the vascular segment is less than a threshold abnormality ratio.

[0012] The step of obtaining the first trend line may include the steps of dividing the vascular region to be analyzed in the medical image into one or more vascular segments, and determining whether or not to merge trend lines calculated for each vascular segment of the one or more vascular segments and vascular segments adjacent to the vascular segment.

[0013] The step of dividing into one or more vascular segments may include a step of dividing the vascular region into the one or more vascular segments based on vascular branches, and the step of determining whether or not the trend lines are merged may include a step of calculating the trend lines for the one or more vascular segments, and a step of determining whether or not the trend lines are merged based on trend values ​​of adjacent positions on the trend lines based on the vascular branches.

[0014] The step of dividing into one or more vascular segments may include a step of determining whether to divide the vascular region into the one or more vascular segments based on the vascular branch based on a diameter value at the vascular branch of a first vascular segment that is closer to an ostium of a coronary artery and a diameter value at the vascular branch of a second vascular segment that is farther from the ostium of the coronary artery, among vascular segments adjacent to each other based on the vascular branch.

[0015] The step of calculating the trend line may include the step of limiting the slope of the trend line that exceeds a reference slope to the reference slope.

[0016] The step of determining whether or not to merge the trend lines may include a step of determining a new trend line by merging the trend line for the first vascular segment and the trend line for the second vascular segment, based on the fact that a trend value for a distal position in a trend line calculated for a first vascular segment that is closer to the entrance of a coronary artery is smaller than a trend value for a proximal position in a trend line calculated for a second vascular segment that is farther from the entrance of the coronary artery.

[0017] The step of determining the lesion candidate includes a step of determining, as the lesion candidate, a portion of a blood vessel region of the medical image that has a diameter smaller than a value obtained by applying a first ratio to the first trend line.

[0018] The step of obtaining a second trend line based on reference points selected from around the lesion candidate can include selecting local peaks around the lesion candidate that have values ​​greater than the first trend line as the reference points.

[0019] The step of selecting as the reference point may include a step of selecting as the reference point a point at which a value corresponding to a diameter of the vascular region is shown among values ​​obtained by applying a threshold reference ratio to the first trend line, based on the local peak exceeding a value obtained by applying a threshold reference ratio to the first trend line.

[0020] The step of selecting as the reference point may include a step of attempting to redetect the local peak based on a value obtained by applying a threshold local ratio to the first trend line based on the fact that at least one of a first reference point (e.g., a proximal reference point) close to the entrance of the coronary artery and a second reference point (e.g., a distal reference point) far from the entrance of the coronary artery is not detected around the lesion candidate.

[0021] The lesion determination method may further include a step of excluding from the determination of the lesion site any lesion candidate for which detection of at least one of a first reference point close to the entrance of the coronary artery and a second reference point far from the entrance of the coronary artery fails.

[0022] The step of determining the lesion site may include a step of determining, as the lesion site, a region of the region corresponding to the lesion candidate that has a diameter smaller than a value obtained by applying a second ratio to the second trend line.

[0023] The step of determining the lesion location can include the step of determining the second ratio based on a value at a corresponding point on the first trend line.

[0024] The step of determining the lesion area may include a step of determining whether to determine the multiple lesion candidates and the intermediate region as a single lesion area based on a ratio between a maximum diameter value and a value along the first trend line at a point corresponding to the maximum diameter value among diameter values ​​in an intermediate region between the multiple lesion candidates when the multiple lesion candidates are adjacent to each other.

[0025] The step of determining the lesion site may include a step of determining that, if multiple lesion candidates are adjacent to each other, the adjacent candidates are to be merged if the distance between the multiple lesion candidates is less than a predetermined value.

[0026] According to one embodiment, an electronic device includes an image acquisition unit that acquires medical images, a display that outputs the medical images, a memory that stores computer-executable instructions, and a processor that executes the instructions stored in the memory. The instructions may be configured to output, together with the medical images, at least one of a first trend line relating to a global trend of blood vessel diameter, a reference point located above the first trend line, a second trend line relating to a local trend of the blood vessel diameter determined based on the reference point, and a lesion site located below the second trend line for each of a plurality of blood vessel segments divided from blood vessels included in the medical images via the display. [Effects of the Invention]

[0027] An electronic device according to an embodiment may improve user convenience by providing automated segmentation and quantitative analysis of vascular images.

[0028] An electronic device according to an embodiment can detect multiple lesions in blood vessels from medical images.

[0029] An electronic device according to one embodiment can provide information about lesions intuitively even to analysts with limited medical experience and / or knowledge by visualizing lesions and trend lines that serve as criteria for lesion assessment. [Brief explanation of the drawings]

[0030] [Figure 1] FIG. 1 shows an electronic device according to one embodiment.

[0031] [Figure 2] FIG. 2 is a flowchart illustrating a lesion determination method according to one embodiment.

[0032] [Figure 3]FIG. 3 illustrates vascular region segmentation and trend line merging according to one embodiment. [Figure 4] FIG. 4 illustrates segmentation of vascular regions and merging of trend lines according to one embodiment. [Figure 5] FIG. 5 illustrates segmentation of vascular regions and merging of trend lines according to one embodiment. [Figure 6] FIG. 6 illustrates segmentation of vascular regions and merging of trend lines according to one embodiment. [Figure 7] FIG. 7 illustrates segmentation of vascular regions and merging of trend lines according to one embodiment. [Figure 8] FIG. 8 illustrates segmentation of vascular regions and merging of trend lines according to one embodiment. [Figure 9] FIG. 9 illustrates segmentation of vascular regions and merging of trend lines according to one embodiment.

[0033] [Figure 10] FIG. 10 illustrates lesion candidate determination according to one embodiment.

[0034] [Figure 11] FIG. 11 illustrates the setting of reference points and obtaining of a second trend line according to one embodiment. [Figure 12] FIG. 12 illustrates the setting of reference points and obtaining of a second trend line according to one embodiment. [Figure 13] FIG. 13 illustrates setting reference points and obtaining a second trend line according to one embodiment. [Figure 14] FIG. 14 illustrates setting reference points and obtaining a second trend line according to one embodiment.

[0035] [Figure 15] FIG. 15 illustrates determining the lesion location according to one embodiment. [Figure 16] FIG. 16 illustrates determining the lesion location according to one embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0036] Specific structural or functional descriptions of the embodiments are disclosed for illustrative purposes only and may be modified in various forms. Therefore, the embodiments are not limited to the specific disclosed forms, and the scope of the present specification includes modifications, equivalents, or alternatives within the technical spirit.

[0037] Although terms such as "first" or "second" may be used to describe multiple components, such terms should be construed only to distinguish one component from the other components. For example, a first component may be named a second component, and similarly, a second component may be named a first component.

[0038] When any component is referred to as being "connected" to another component, it is directly linked or connected to the other component, but it should be understood that there may be other components in between.

[0039] The singular expression includes the plural expression unless the context clearly dictates otherwise. In this specification, the words "comprise" or "have" and the like indicate the presence of features, numbers, steps, operations, components, parts, or combinations thereof described in the specification, and should be understood as not precluding the possibility of the presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

[0040] Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by a person of ordinary skill in the art to which the present invention belongs. Commonly used predefined terms should be interpreted as having a meaning consistent with the meaning they have in the context of the relevant art, and should not be interpreted as having an ideal or overly formal meaning unless expressly defined herein.

[0041] Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. When describing with reference to the drawings, the same reference numerals will be used to designate the same elements, regardless of the reference numerals, and redundant description thereof will be omitted.

[0042] FIG. 1 shows an electronic device according to one embodiment.

[0043] The electronic device 100 according to an embodiment is a device for analyzing medical images, and includes an image acquisition unit 130, a processor 110, a display 140, and a memory 120.

[0044] The image acquisition unit 130 acquires a medical image 131. The medical image 131 capturing blood vessels of a target object (e.g., a patient 190) may also be displayed as a blood vessel image. For example, the image acquisition unit 130 may include an X-ray imaging device and capture the medical image 131 (e.g., an X-ray-based CAG image) through an X-ray-based coronary angiography (hereinafter, "CAG").

[0045] The medical image 131 may include one or more frames. To image blood vessels, a contrast agent is injected into the blood vessels of the subject 190, and the blood vessels of the subject 190 are imaged while the contrast agent is being maintained. Among the frames of the medical image 131, a frame in which the contrast agent is observed may be referred to as a contrast agent frame. In an X-ray-based CAG image, the intensity value of each pixel is the intensity due to the penetration of X-rays, and the intensity value at the point where the X-rays are absorbed by the contrast agent is displayed as low. In this specification, an image of a contrast agent frame among X-ray-based CAG images will be mainly described as an example of the medical image 131. However, this is for convenience of explanation, and the present invention is not limited thereto. The operations described below with reference to FIGS. 2 to 16 for lesion determination may also be applied to other medical images in which blood vessels are imaged.

[0046] For reference, an example has been described in which the image acquisition unit 130 has X-ray imaging equipment to capture medical images 131, but this is not limited to this, and the image acquisition unit 130 can also include a communication module for wired communication and / or wireless communication and receive vascular images (e.g., CAG images based on X-rays) from an external imaging device via the communication module.

[0047] The processor 110 may output, together with the medical image, at least one of a first trend line relating to a global trend of blood vessel diameter, a reference point located above the first trend line, a second trend line relating to a local trend of blood vessel diameter determined based on the reference point, and a lesion location located below the second trend line for each of a plurality of blood vessel segments divided from a blood vessel included in the medical image, via the display 140. The first trend line may be represented as a global trend line, and the second trend line may be represented as a local trend line. The processor 110 may select at least one of the first trend line, the reference point, the second trend line, and the lesion location based on input from a user (e.g., an analyst). The processor 110 may output a graphic representation indicating the selected information using the display 140. The operation of the processor 110 will be described below with reference to FIGS. 2 to 16. For example, the acquisition of the first trend line will be described with reference to Figures 3 to 9 below, the determination of lesion candidates with reference to Figure 10 below, the setting of reference points and the acquisition of the second trend line with reference to Figures 11 to 14 below, and the determination of the lesion site with reference to Figures 15 and 16 below.

[0048] The display 140 outputs the medical image 131. The processor 110 can also visualize (e.g., overlay) a graphical representation indicating at least one of the first trend line, the reference point, the second trend line, and the lesion location on the medical image 131 via the display 140.

[0049] The memory 120 stores at least some or all frames of the medical image 131. The memory 120 stores information about the detected lesion (e.g., the location, size, and blood vessel diameter of the lesion), and can temporarily and / or permanently store data and / or information required to perform a method for lesion determination through analysis of the medical image 131.

[0050] The electronic device 100 according to an embodiment can intuitively provide vascular information for quantitatively assessing the severity of a lesion. The electronic device 100 can automatically identify not only lesion candidates but also reference points for determining whether a lesion is present. The electronic device 100 can also identify multiple lesions in a single blood vessel.

[0051] FIG. 2 is a flowchart illustrating a lesion determination method according to one embodiment.

[0052] First, in step 210, an electronic device (e.g., electronic device 100 of FIG. 1) obtains a first trend line related to the diameter of a blood vessel from a medical image. As described above with reference to FIG. 1, the medical image may be, but is not limited to, an X-ray-based CAG image. The diameter of a blood vessel indicates the inner diameter through which blood can flow. Although the present specification mainly refers to the diameter for convenience of explanation, the present specification is not limited to this and may also be expressed as the width of the blood vessel. The first trend line may also be displayed as a global trend line, which indicates the global trend of the blood vessel area and / or blood vessel segments divided from the blood vessel area.

[0053] Then, in step 220, the electronic device determines lesion candidates within the blood vessel based on the first trend line. The lesion candidates indicate portions of the blood vessel that may be candidates for potential lesions. The electronic device may determine a portion of the blood vessel as a lesion candidate based on the difference between values ​​along the first trend line (e.g., a first trend value) for the portion and diameter values ​​for the portion. The values ​​along the trend line may also be referred to as trend values. Determining lesion candidates based on the first trend value and diameter values ​​is described with reference to FIG. 10 below. The trend values ​​may also be used to determine whether to merge trend lines, as described with reference to FIGS. 6 and 7 below.

[0054] Next, in step 230, the electronic device acquires a second trend line based on a reference point selected from the periphery of the lesion candidate. The peripheral region of the lesion candidate includes a region adjacent to the lesion candidate laterally in the direction close to the coronary artery ostium (e.g., a proximal region) and a region adjacent to the lesion candidate in a direction away from the coronary artery ostium (e.g., a distal region). In this specification, the coronary artery exemplarily refers to the entire tree-structured blood vessels branching from the aortic root and extending toward the heart. The electronic device may set a reference point in the periphery of the lesion candidate based on the first trend line. The reference point will be described later; it is a point on a blood vessel diameter graph that serves as a reference for acquiring the second trend line. The electronic device can acquire the second trend line by connecting two reference points that are set adjacent to each other. The setting of the reference point and acquisition of the second trend line will be described with reference to FIGS. 11 to 14 below.

[0055] Then, in step 240, the electronic device determines a lesion location among the lesion candidates based on the acquired second trend line. The electronic device may determine at least some of the locations corresponding to the lesion candidates as the lesion location, or may exclude some of the multiple lesion candidates from the lesion location determination. The determination of the lesion location will be described below with reference to Figures 15 and 16.

[0056] 3-9 illustrate the segmentation of vascular regions and merging of trend lines according to one embodiment.

[0057] FIG. 3 is a flowchart illustrating the segmentation of vessel regions and the merging of trend lines. The trend lines described with reference to FIGS. 3 to 9 are first trend lines, e.g., global trend lines relating to the global trends of vessel regions and / or vessel segments. For reference, this specification primarily describes the analysis target as extending from the entrance of the coronary artery to the terminal vessels of each branch, but is not limited thereto. For example, an electronic device (e.g., electronic device 100 of FIG. 1) may determine whether to include a vessel bifurcation in the analysis target based on the diameter of the vessel bifurcation. The electronic device may exclude a vessel bifurcation from the analysis target if its diameter is less than an analysis threshold, and include a vessel bifurcation in the analysis target if its diameter is equal to or greater than the analysis threshold.

[0058] First, in step 311, the electronic device calculates the diameter of the blood vessel region 480 to be analyzed from the medical image 400. For example, the electronic device can calculate the diameter within the blood vessel region 480 for each position along the centerline 410 based on a line 420 perpendicular to the centerline 410 of the blood vessel region 480 to be analyzed in the medical image 400. The centerline 410 of the blood vessel region 480 is a line that passes through the center of the blood vessel and connects the center points of the blood vessel inner diameters longitudinally. A position along the centerline 410 indicates a position that is a certain distance away from the start position 401 along the centerline 410. The diameter at a position along the centerline 410 indicates the length (or distance) between the blood vessel inner walls along the line 420 perpendicular to the centerline 410 at that position. The electronic device can obtain blood vessel diameter information indicating the blood vessel diameter for each position along the centerline 410. In FIG. 4, the blood vessel diameter information is shown in a blood vessel diameter graph 490. The blood vessel diameter graph 490 includes, for example, a graph showing a diameter of y mm at a position x mm (millimeters) away from the start position 401 along the center line 410. For reference, the start position 401 may be, for example, a point indicating the entrance of a coronary artery, but is not limited to this and may vary depending on the design. For example, the start position 401 may be set as the start point of a blood vessel segment, as the point in the blood vessel segment closest to the entrance of a coronary artery.

[0059] The electronic device according to an embodiment can obtain a first trend line based on the diameter calculated as described above. For example, the electronic device can calculate the first trend line for a blood vessel segment divided from the blood vessel region 480, which will be described later.

[0060] For example, in step 312, the electronic device divides the vascular region into one or more vascular segments. An electronic device according to an embodiment may divide a vascular region to be analyzed in a medical image into one or more vascular segments. For example, the electronic device may divide the vascular region into one or more vascular segments based on vessel bifurcation. In the process of dividing the vascular region into one or more vascular segments, vascular bifurcation excluded from the analysis target may also be used as a basis for division. For reference, an electronic device according to an embodiment may skip determining lesion candidates and / or lesion sites for regions corresponding to vascular bifurcation.

[0061] For example, the electronic device may determine whether to divide a vascular region into one or more vascular segments based on vascular branches based on a diameter value of a vascular branch of a first vascular segment that is close to the coronary artery ostium and a diameter value of a vascular branch of a second vascular segment that is far from the coronary artery ostium, among vascular segments adjacent to each other based on the vascular branch. The diameter value of the vascular branch of the first vascular segment is the diameter value at a position far from the coronary artery ostium within the first vascular segment, and is therefore referred to as the distal diameter value of the first vascular segment. Similarly, the diameter value of the vascular branch of the second vascular segment is referred to as the proximal diameter value of the second vascular segment.

[0062] The electronic device can determine whether to divide the first and second vessel segments into separate segments based on a difference between a distal diameter value of the first vessel segment and a proximal diameter value of the second vessel segment. The electronic device divides the first and second vessel segments based on the difference between the distal diameter value of the first vessel segment and the proximal diameter value of the second vessel segment exceeding a division threshold. The electronic device can determine that the first and second vessel segments are the same vessel segment based on the difference between the distal diameter value of the first vessel segment and the proximal diameter value of the second vessel segment being equal to or less than the division threshold.

[0063] 5 shows an example in which the vascular region is divided into a first intermediate segment 520 and a second intermediate segment 530 based on a first branch 502, and into a second intermediate segment 530 and a distal segment 540 based on a second branch 503. Furthermore, if the coronary artery entrance 590 is included in the vascular region, the segments can be divided (e.g., the segment boundaries can be specified) based on the coronary artery entrance 590. The same method is applied to the division into a proximal segment 510 and a first intermediate segment 520 based on a position 501 where the left anterior descending artery (LAD) and the left circumflex artery (LCX) branch off from the left main (LM).

[0064] Next, in step 313, the electronic device calculates trend lines for one or more vessel segments. In one embodiment, the electronic device may calculate a regression line for one or more vessel segments based on a regression analysis using a prior slope. The prior slope indicates a slope set as an initial value for the regression analysis and has different values ​​depending on the position of the vessel segment. For example, the prior slope of a vessel segment located at a certain position may be different from the prior slope of another vessel segment located at a different position. The electronic device may eliminate outliers selected based on the prior regression line calculated from diameters at positions along the centerline of the vessel segment. An outlier is an abnormal value among diameter values. For example, the electronic device may determine, as an outlier, a diameter value at a position along the centerline of the vessel segment that exceeds a range determined based on the prior regression line. The electronic device may determine, as an outlier, a diameter value that exceeds a range of [value along the regression line + a * std, value along the regression line + b * std] based on the regression line (or the prior regression line). std is the standard deviation of the regression line, and a and b are real numbers that represent weights for setting the range for determining outliers. The electronic device can calculate the regression line based on the diameter from which the outliers have been excluded.

[0065] The electronic device can repeat the process of removing outliers and calculating regression lines until the ratio of diameters determined to be outliers to diameters at positions along the centerline within the blood vessel segment is less than a threshold abnormality ratio (e.g., n%, where n is a real number greater than 0 and less than 100). The electronic device can determine a regression line showing outliers less than the threshold abnormality ratio as a first trend line for the blood vessel segment.

[0066] Then, in step 314, the electronic device determines whether to merge the trend lines calculated for each of the one or more vessel segments and vessel segments adjacent to the one or more vessel segments (e.g., the trend lines calculated in step 313 described above). One or more vessel segments are segmented from the vessel region being analyzed in the medical image. The electronic device determines whether to merge the trend lines based on trend values ​​at positions adjacent to the vessel branches on the trend lines. The trend value at any position in the vessel region and / or vessel segment (e.g., a position x mm away from the starting position) indicates a value along the trend line corresponding to that position (e.g., a position x mm away from the starting position), as described above.

[0067] For example, the electronic device can determine a new trend line by merging the trend line for the first vessel segment and the trend line for the second vessel segment based on the fact that a distal trend value (e.g., a distal trend value) in a trend line calculated for a first vessel segment that is closer to the coronary artery entrance among adjacent vessel segments is smaller than a proximal trend value (e.g., a proximal trend value) in a trend line calculated for a second vessel segment that is farther from the coronary artery entrance. The electronic device can determine a new first trend line for the vessel segment determined as the merged trend line based on regression analysis.

[0068] For example, in the example shown in FIG. 6 , the electronic device may determine whether to merge the first trend line 639 of the second middle segment 630 and the first trend line 649 of the distal segment 640. In the example shown in FIG. 6 , the trend lines 639, 649 for the second middle segment 630 and the distal segment 640 are merged because the distal trend value 631 of the second middle segment 630 is less than the proximal trend value 641 of the distal segment 640. The electronic device may also determine whether to merge based on the difference 651 between the distal trend value 631 of the second middle segment 630 and the proximal trend value 641 of the distal segment 640. The electronic device merges the trend lines 639, 649 based on the difference 651 between the segment trend values ​​at the vessel branch 650 being equal to or less than a merge threshold. Conversely, merging of trend lines 639, 649 may be skipped based on the difference 651 between the trend values ​​exceeding a merging threshold. The electronic device determines a new first trend line 670 using the diameter value 690 belonging to the second intermediate segment 630 and the diameter value 690 belonging to the distal segment 640. Diameter values ​​of the branch vessels between the second intermediate segment 630 and the distal segment 640 are excluded from the trend line calculation.

[0069] In addition, the electronic device may determine whether or not to merge the trend lines 639, 649 of the divided vessel segments, starting from the vessel segment farthest from the coronary artery entrance to the vessel segment closest to the coronary artery entrance. In Figure 6, a new first trend line 670 is obtained by merging the trend lines 639, 649 of the distal segment 640 farthest from the coronary artery entrance and the second intermediate segment 630. Thereafter, the electronic device may also determine whether or not to merge the trend lines of the first intermediate segment 620 and the proximal segment 610.

[0070] For example, in FIG. 7 , the electronic device can determine whether to merge a new first trend line 770 (e.g., first trend line 670 merged in FIG. 6 ) for the second intermediate segment 730 and the distal segment 740 into the first intermediate segment 720 based on the trend value difference 751 at the branch vessel 750. In the example shown in FIG. 7 , the distal trend value 721 of the trend line 729 calculated for the first intermediate segment 720 may be greater than the proximal trend value 731 of the new first trend line 770. The electronic device skips merging between the first trend line 729 calculated for the first intermediate segment 720 and the new first trend line 770. The electronic device can resume determining whether to merge trend lines from the first intermediate segment 720. For example, the electronic device may determine whether to merge the trend lines of the proximal segment 710 and the first intermediate segment 720 based on the difference between the distal trend value of the trend line 719 of the proximal segment 710 and the proximal trend value of the trend line 729 of the first intermediate segment 720 relative to the blood vessel branch 760. Because the distal trend value of the trend line 719 of the proximal segment 710 is less than the proximal trend value of the trend line 729 of the first intermediate segment 720, the electronic device may merge the trend lines of the proximal segment 710 and the first intermediate segment 720 to determine a different new first trend line 780. As a result, in the example shown in FIG. 7 , the electronic device may obtain a merged new first trend line 770 for the second intermediate segment 730 and the distal segment 740, and a different merged new first trend line 780 for the proximal segment 710 and the first intermediate segment 720.

[0071] For reference, as shown in FIG. 8, the electronic device can determine an upper limit for the slope of the trend line for each vessel segment. For example, the electronic device can limit the slope of any trend line that exceeds a reference slope to the reference slope. In the example shown in FIG. 8, the reference slope can be set to zero. If the slope of trend line 848 calculated based on diameter values ​​890 for distal segment 840 exceeds zero, the electronic device can obtain a new first trend line 849 with a slope of zero.

[0072] FIG. 9 shows an exemplary first trend line obtained based on the linear regression and trend line merging described above.

[0073] An electronic device according to an embodiment may visualize a first trend line 909 obtained as described above with reference to FIGS. 3 to 8. In the example shown in FIG. 9, the first trend line 909 may be a trend line obtained for one or more blood vessel segments. The electronic device may output the first trend line 909 via a display along with a graph for the diameter values ​​990. When visualization of the first trend line 909 is activated by a user input, the electronic device may overlay and display the first trend line 909 on the graph for the diameter values ​​990. For reference, in the graph for the diameter values ​​990, the horizontal axis indicates the distance from the start position to each individual position, and the vertical axis indicates the diameter value at each position.

[0074] FIG. 10 illustrates lesion candidate determination according to one embodiment.

[0075] An electronic device according to an embodiment may determine a lesion candidate 1020 based on the first trend line 1009, as described in step 220 of FIG. 2 . For example, the electronic device may determine, as the lesion candidate 1020, a portion of the diameter values ​​1090 of a blood vessel region of a medical image that has a diameter smaller than a value obtained by applying a first ratio to the first trend line 1009. Exemplarily, the first ratio may be a real number greater than 0 and less than 1, and the electronic device may determine, as the lesion candidate 1020, a portion of the blood vessel region having a diameter value equal to or smaller than the line 1010 obtained by multiplying the first trend line 1009 by the first ratio. In FIG. 10 , the first ratio is shown as the same value for the entire region, but is not limited thereto. For reference, the electronic device may visualize the lesion candidate 1020 with a graph of the diameter values ​​1090.

[0076] 11 to 14 illustrate the setting of reference points and the acquisition of the second trend line according to one embodiment.

[0077] In step 1131, an electronic device (e.g., electronic device 100 of FIG. 1) selects local peaks around the lesion candidate that have values ​​greater than the first trend line as reference points. The electronic device selects local peaks around the lesion candidate that have values ​​greater than the first trend line as reference points. For example, in the example shown in FIG. 12, the electronic device may select local peaks 1211, 1212, 1221, 1222, and 1231 that have values ​​equal to or greater than the first trend line 1209 as reference points. As described above, the portions of diameter value 1290 that are equal to or less than the first trend line 1209 may be determined to be lesion candidates 1210 and 1220 as described above. For each lesion candidate, reference points adjacent to the coronary artery entrance are shown as first reference points 1211, 1221, 1231 (eg, proximal reference points), and reference points further from the coronary artery entrance are shown as second reference points 1212, 1222 (eg, distal reference points).

[0078] As shown in FIG. 12 , a pair of reference points must be detected for each lesion candidate; however, only one reference point may be detected for some lesion candidates. For example, the electronic device may exclude a lesion candidate for which at least one of the first reference point near the coronary artery entrance and the second reference point far from the coronary artery entrance is not detected from the lesion location determination. However, without being limited thereto, if some reference points are not found in the anterior-posterior regions of the lesion candidate, the electronic device may re-search for reference points based on a line (not shown) obtained by decreasing the first trend line 1209. For example, if at least one of the first reference point near the coronary artery entrance and the second reference point far from the coronary artery entrance (e.g., the distal reference point paired with the first reference point 1231 in FIG. 12 ) is not detected around the lesion candidate, the electronic device may attempt to re-detect a local peak based on a value obtained by applying a threshold local ratio to the first trend line 1209. The threshold local ratio may be a real number greater than 0 and less than 1. The electronic device can detect local peaks higher than a line (not shown) obtained by multiplying the first trend line 1209 by a threshold local ratio, in which case lesion candidates that fail local peak detection can still be excluded from determining the lesion site.

[0079] Then, in step 1132, the electronic device determines a reference point 1322 based on the first trend line if the local peak exceeds a value corresponding to a threshold reference ratio. For example, the electronic device may select, as reference point 1322, a point at which a value corresponding to the diameter of the vascular region is shown among the values ​​obtained by applying a threshold reference ratio (e.g., K, where K is a real number greater than or equal to 1) to the first trend line, based on the local peak exceeding a value obtained by applying a threshold reference ratio (e.g., K, where K is a real number greater than or equal to 1) to the first trend line. In the example shown in FIG. 13 , the electronic device can detect a local peak 1321 on the first trend line 1309. If the difference 1329 between the local peak 1321 and the first trend line 1309 exceeds a threshold, the electronic device can set another point as the reference point 1322 instead of the local peak 1321. For example, the electronic device can select the point where the line 1310 intersects with the graph corresponding to the diameter value 1390 as the reference point 1322 based on the local peak 1321 being higher than the line 1310 obtained by multiplying the first trend line by a threshold reference ratio.

[0080] Next, in step 1133, the electronic device obtains a second trend line 1450 by connecting the reference points for each lesion candidate. For example, as shown in FIG. 14 , the electronic device can obtain a second trend line 1450 by connecting the first reference points 1411 and 1421 and the second reference points 1412 and 1422 for each lesion candidate. In step 1131, as described above, the second trend line 1450 is generated only for pairs of reference points, and the generation of the second trend line and the determination of the lesion location are excluded for reference points where one of the proximal and distal reference points is missing (e.g., reference point 1431 in FIG. 14 ).

[0081] As described above, an electronic device according to an embodiment may visualize the acquired reference points and second trend line. For example, the electronic device may visualize at least one of the reference points and the second trend line by overlaying them on a graph for the diameter value 1490. The electronic device may output, using a display, a graphical representation of the reference points and the second trend line that corresponds to an item activated by a user input, along with the graph for the diameter value.

[0082] 15 and 16 illustrate determining the lesion location according to one embodiment.

[0083] FIG. 15 explains the operation of determining a lesion site from among lesion candidates.

[0084] An electronic device (e.g., electronic device 100 of FIG. 1 ) according to an embodiment can determine a lesion location from a lesion candidate based on a second trend line, as described in step 240 of FIG. 2 . For example, the electronic device can determine, as the lesion location, a region corresponding to the lesion candidate that has a diameter smaller than the value obtained by applying a second ratio to the second trend line. In the example shown in FIG. 15 , the electronic device can determine, as the lesion location, a portion that is lower than lines 1561 and 1562 obtained by applying the second ratio to second trend lines 1551 and 1552. The second ratio (e.g., m) is a real number greater than 0 and less than 1 and may have different values ​​for each lesion candidate and / or location. For example, although FIG. 15 illustrates the second ratio as having the same value for second trend line 1551 for the first lesion candidate and second trend line 1552 for the second lesion candidate, this is not limiting. For example, the electronic device can determine the second ratio based on the value of a corresponding point on the first trend line. The electronic device may set the second ratio value applied to the second lesion candidate located distally relative to the coronary artery entrance to be smaller than the second ratio value applied to the first lesion candidate located proximally. For example, the electronic device may apply a second ratio value of 0.7 to the first lesion candidate located proximally and a second ratio value of 0.5 (or 0.3) to the second lesion candidate located distally. In other words, it can be understood that the lesion location is determined relatively conservatively for the first lesion candidate located proximally compared to the second lesion candidate located distally. The electronic device may also visualize the second trend lines 1551, 1552 together with a graph of the diameter value 1590.

[0085] FIG. 16 explains the operation of determining whether adjacent lesion sites should be recognized as one lesion.

[0086] An electronic device according to one embodiment (e.g., electronic device 100 of FIG. 1 ) determines that lesion sites 1681 and 1682 are included in the same lesion based on the fact that lesion sites 1681 and 1682 determined based on second trend line 1651 are detected below the first trend line. In the example shown in FIG. 16 , two lesion sites 1681 and 1682 may be detected for one lesion candidate below line 1652, which is obtained by applying a second ratio to second trend line 1651. In this case, the electronic device determines that the two lesion sites 1681 and 1682 are a single lesion based on the fact that a local peak shown in the intermediate region between them is smaller than the first trend line.

[0087] As another example, when multiple lesion candidates are adjacent to each other, the electronic device determines whether to determine the multiple lesion candidates and intermediate region as a single lesion region based on the ratio between the maximum diameter value and a value along a first trend line at a point corresponding to the maximum diameter value (e.g., a first trend value) among diameter values ​​1690 in an intermediate region between the multiple lesion candidates. For example, in the example shown in FIG. 16 , the electronic device may extract the maximum diameter value among diameter values ​​1690 in the intermediate region between first lesion region 1681 and second lesion region 1682. The electronic device may determine that two lesion regions 1681 and 1682 are included in the same lesion based on the ratio between the extracted maximum diameter value and the first trend value at that position being within a predetermined range (e.g., a range including 1). The closer the ratio between the extracted maximum diameter value and the first trend value at that position is to 1, the more likely it is that the two lesion regions 1681 and 1682 are included in the same lesion.

[0088] As another example, the electronic device may determine whether adjacent candidates among a plurality of lesion candidates belong to the same lesion based on the distance between the adjacent candidates. When multiple lesion candidates are adjacent to each other, the electronic device may determine to merge the adjacent candidates if the distance between the multiple lesion candidates is less than a predetermined value. For example, the electronic device may determine to merge two lesion candidates into one lesion if the distance between the two lesion candidates is less than 15 mm. Here, the predetermined value may be, but is not limited to, a value equal to or less than 15 mm, and the predetermined value may vary depending on a user setting.

[0089] In one embodiment, the electronic device can select at least one of the first trend line 1609, the lesion candidate, the reference point, the second trend line 1651 based on the reference point, and the lesion site 1681, 1682 determined based on the second trend line based on user input, and visualize a graphical representation corresponding to the selected item using a display along with a graph of the diameter value 1690.

[0090] The above-described embodiments may be implemented using hardware components, software components, or a combination of hardware and software components. For example, the devices and components described herein may be implemented using one or more general-purpose or special-purpose computers, such as a processor, controller, arithmetic logic unit (ALU), digital signal processor, microcomputer, field programmable array (FPA), programmable logic unit (PLU), microprocessor, or other device that executes and responds to instructions. The processing device executes an operating system (OS) and one or more software applications that run on the operating system. The processing device also accesses, stores, manipulates, processes, and generates data in response to the execution of the software. For ease of understanding, a single processing device may be described; however, those skilled in the art will recognize that a processing device may include multiple processing elements and / or multiple types of processing elements. For example, a processing device may include multiple processors or one processor and one controller. Other processing configurations, such as parallel processors, are also possible.

[0091] Software includes computer programs, codes, instructions, or a combination of one or more thereof, which can configure a processing device to operate as desired or can independently or in combination instruct the processing device. The software and / or data can be permanently or temporarily embodied in any type of machine, component, physical device, virtual device, computer storage medium or device, or transmitted signal wave to be interpreted by or provide instructions or data to a processing device. The software can be distributed across computer systems coupled to a network and stored and executed in a distributed manner. The software and data can be stored on one or more computer-readable recording media.

[0092] The method according to the present invention may be embodied in the form of program instructions that can be executed by various computer means and recorded on a computer-readable recording medium. The recording medium may include program instructions, data files, data structures, and the like, alone or in combination. The recording medium and program instructions may be specially designed and constructed for the purposes of the present invention, or may be well-known and available to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tape, optical media such as CD-ROMs and DVDs, magneto-optical media such as floptical disks, and hardware devices specially configured to store and execute program instructions, such as ROM, RAM, flash memory, and the like. Examples of program instructions include not only machine language code, such as that generated by a compiler, but also high-level language code that is executed by a computer using an interpreter, for example.

[0093] The hardware devices described above may be configured to operate as one or more software modules to perform the operations described in this invention, and vice versa.

[0094] Although the embodiments have been described above with reference to limited drawings, those skilled in the art may apply various technical modifications and variations based on the above description. For example, the described techniques may be performed in a different order than described, and / or the components of the described systems, structures, devices, circuits, etc. may be combined or combined in a different manner than described, and may be replaced or substituted with other components or equivalents, while still achieving suitable results.

[0095] Accordingly, other implementations, other embodiments, and equivalents of the claims are intended to fall within the scope of the following claims. The inventions disclosed herein include the following: [Aspect 1] 1. A method of lesion determination performed by a processor, comprising: obtaining a first trendline for vessel diameter from a medical image; determining a lesion candidate from the blood vessel based on the first trend line; obtaining a second trend line based on reference points selected from around the suspected lesion; determining a lesion site among the lesion candidates based on the acquired second trend line; A method for determining a lesion, comprising: [Aspect 2] The step of obtaining the first trend line includes: Segmenting one or more vessel segments from a vessel region of interest in the medical image; determining whether the trend lines calculated for each of the one or more vessel segments and vessel segments adjacent to the one or more vessel segments merge; 2. The lesion determination method of embodiment 1, comprising: [Aspect 3] the dividing into one or more vascular segments comprises dividing the vascular region into the one or more vascular segments based on vascular branches; The step of determining whether or not the trend lines are merged comprises: calculating the trend line for the one or more vessel segments; determining whether the trend lines merge based on diameter values ​​at adjacent positions on the trend lines relative to the blood vessel branch; 3. The lesion determination method according to embodiment 2, comprising: [Aspect 4] A lesion determination method as described in aspect 3, wherein the step of dividing into one or more vascular segments includes a step of determining whether to divide the vascular region into the one or more vascular segments based on the vascular branch based on a diameter value at the vascular branch of a first vascular segment that is close to the entrance of the coronary artery and a diameter value at the vascular branch of a second vascular segment that is far from the entrance of the coronary artery, among vascular segments adjacent to each other based on the vascular branch. [Aspect 5] The lesion determination method of aspect 2, wherein the step of determining whether or not the trend lines are merged includes a step of determining a new trend line by merging the trend line for the first vascular segment and the trend line for the second vascular segment based on the fact that the diameter value at the distal position of the trend line calculated for the first vascular segment, which is closer to the entrance of the coronary artery, is smaller than the diameter value at the proximal position of the trend line calculated for the second vascular segment, which is farther from the entrance of the coronary artery. [Aspect 6] The lesion determination method according to aspect 1, wherein the step of determining the lesion candidate includes a step of determining, as the lesion candidate, a portion of the vascular region of the medical image that has a diameter smaller than the value obtained by applying a first ratio to the first trend line. [Aspect 7] The lesion determination method of aspect 1, wherein the step of obtaining a second trend line based on a reference point selected from around the lesion candidate includes a step of selecting a local peak in the vicinity of the lesion candidate that has a value greater than that of the first trend line as the reference point. [Aspect 8] The lesion determination method of aspect 7, wherein the step of selecting as the reference point includes a step of selecting as the reference point a point, among values ​​obtained by applying a threshold reference ratio to the first trend line, that shows a value corresponding to the diameter of the vascular region, based on the local peak exceeding a value obtained by applying a threshold reference ratio to the first trend line. [Aspect 9] The lesion determination method of aspect 1, wherein the step of determining the lesion site includes a step of determining, as the lesion site, a region of the region corresponding to the lesion candidate that has a diameter smaller than the value obtained by applying a second ratio to the second trend line. [Aspect 10] The lesion determination method of aspect 1, wherein the step of determining the lesion site includes a step of, when multiple lesion candidates are adjacent to each other, determining whether to determine the multiple lesion candidates and the intermediate region as a single lesion site based on the ratio between the maximum diameter value and the value along the first trend line at the point corresponding to the maximum diameter value among diameter values ​​within the intermediate region between the multiple lesion candidates. [Aspect 11] The lesion determination method of aspect 1, wherein the step of determining the lesion site includes a step of determining that, when multiple lesion candidates are adjacent to each other, the adjacent candidates are to be merged if the distance between the multiple lesion candidates is less than a predetermined value. [Aspect 12] 1. An electronic device, comprising: an image acquisition unit that acquires medical images; a display for outputting the medical image; a memory for storing computer-executable instructions; a processor that executes the instructions stored in the memory; Including, The electronic device is configured to output, together with the medical image, at least one of a first trend line relating to a global trend of blood vessel diameter for each of a plurality of blood vessel segments divided from a blood vessel included in the medical image, a reference point located above the first trend line, a second trend line relating to a local trend of the blood vessel diameter determined based on the reference point, and a lesion site located below the second trend line, for each of a plurality of blood vessel segments divided from a blood vessel included in the medical image, via the display.

Claims

1. 1. A method of lesion determination performed by a processor, comprising: obtaining a first trendline for vessel diameter from a medical image; determining a lesion candidate from the blood vessel based on the first trend line; obtaining a second trend line based on reference points selected from the periphery of the suspected lesion; determining a lesion site among the lesion candidates based on the acquired second trend line; Including, The step of obtaining the first trend line includes: Dividing a vascular region to be analyzed in the medical image into two or more vascular segments; determining whether the trend lines calculated for each of the two or more vessel segments and the vessel segments adjacent to the vessel segment merge; A method for determining a lesion, comprising:

2. the dividing the vascular region into two or more vascular segments includes dividing the vascular region into the two or more vascular segments based on vascular branches; The step of determining whether or not the trend lines are merged comprises: calculating the trend lines for the two or more vessel segments; determining whether the trend lines merge based on diameter values ​​at adjacent positions on the trend lines relative to the blood vessel branch; The method of claim 1 , comprising:

3. 3. The lesion determination method according to claim 2, wherein the step of dividing the vascular region into two or more vascular segments includes a step of determining whether to divide the vascular region into the two or more vascular segments based on the vascular branch based on a diameter value at the vascular branch of a first vascular segment that is closer to an entrance of a coronary artery and a diameter value at the vascular branch of a second vascular segment that is farther from the entrance of the coronary artery, among vascular segments adjacent to each other based on the vascular branch.

4. 2. The lesion determination method of claim 1, wherein the step of determining whether or not the trend lines should be merged includes a step of determining a new trend line by merging the trend line for the first vascular segment and the trend line for the second vascular segment, based on the fact that a diameter value at a distal position of a trend line calculated for a first vascular segment that is closer to an entrance of a coronary artery is smaller than a diameter value at a proximal position of a trend line calculated for a second vascular segment that is farther from the entrance of the coronary artery.

5. 2. The lesion determination method according to claim 1, wherein the step of determining the lesion candidate includes a step of determining, as the lesion candidate, a portion of a vascular region of the medical image that has a diameter smaller than a value obtained by applying a first ratio to the first trend line.

6. 2. The method of claim 1, wherein the step of obtaining a second trend line based on reference points selected from around the lesion candidate comprises the step of selecting local peaks around the lesion candidate that have values ​​greater than the first trend line as the reference points.

7. 7. The method of claim 6, wherein the step of selecting as the reference point comprises the step of selecting as the reference point a point at which a value corresponding to a diameter of the vascular region is shown among values ​​obtained by applying a threshold reference ratio to the first trend line, based on the local peak exceeding a value obtained by applying a threshold reference ratio to the first trend line.

8. 2. The lesion determination method according to claim 1, wherein the step of determining the lesion site includes a step of determining, as the lesion site, a region of the region corresponding to the lesion candidate that has a diameter smaller than a value obtained by applying a second ratio to the second trend line.

9. 2. The method of claim 1, wherein the step of determining the lesion area includes, when a plurality of lesion candidates are adjacent to each other, determining whether to determine the plurality of lesion candidates and the intermediate region as a single lesion area based on a ratio between a maximum diameter value among diameter values ​​in an intermediate region between the plurality of lesion candidates and a value along the first trend line at a point corresponding to the maximum diameter value.

10. 1. An electronic device, comprising: an image acquisition unit that acquires medical images; a display for outputting the medical image; a memory for storing computer-executable instructions; a processor that executes the instructions stored in the memory; Including, The command is configured to output, via the display, at least one of a first trend line relating to a global trend of blood vessel diameters for each of a plurality of blood vessel segments divided from a blood vessel included in the medical image, a reference point located above the first trend line, a second trend line relating to a local trend of the blood vessel diameters determined based on the reference point, and a lesion site located below the second trend line together with the medical image; The processor: To obtain the first trend line, an electronic device divides the vascular region to be analyzed in the medical image into two or more vascular segments, and determines whether or not trend lines calculated for each of the two or more vascular segments and vascular segments adjacent to the vascular segment merge.

Images