Method and electronic device for correcting pressure difference value of blood vessel

Abstract

Disclosed is a method by which at least one processor corrects a pressure difference value of a blood vessel, the method comprising the steps of: acquiring at least one image obtained by capturing the blood vessel of a subject with an imaging device and imaging information of the imaging device for the at least one image; acquiring, on the basis of the imaging information, height information in the gravity direction of the blood vessel included in the at least one image; calculating a height difference value between a first point and a second point of the blood vessel on the basis of the height information; calculating a pressure difference value due to gravity between the first point and the second point of the blood vessel on the basis of the difference value in height; and correcting the pressure difference value between the first point and the second point of the blood vessel on the basis of the pressure difference value due to gravity.

Description

Method and electronic device for compensating for pressure difference values ​​in blood vessels

[0001] The present disclosure relates to a method and an electronic device for compensating a pressure difference value in a blood vessel.

[0002] The coronary arteries are the arteries that surround the heart and supply oxygen and nutrients to the myocardium, the heart muscle. The heart's function depends on the continuous supply of oxygen and nutrients from the coronary arteries. Therefore, if an abnormality (e.g., disease) occurs in the coronary arteries, preventing the myocardium from receiving adequate oxygen and nutrients, cardiovascular diseases such as myocardial infarction can occur.

[0003] To quickly and accurately diagnose vascular lesions such as coronary artery stenosis, blood flow characteristic values ​​such as fractional flow reserve (FFR) can be utilized for diagnosis. For example, when a lesion develops in a coronary artery, the blood flow passes through the lesion, causing a drop in pressure due to the loss of kinetic energy (perfusion pressure), resulting in a pressure difference between the distal and proximal parts of the lesion. This pressure difference can be measured using a pressure wire, an FFR device.

[0004] However, in addition to the pressure loss due to the narrowing of the lesion's internal diameter, the pressure (e.g., hydrostatic pressure) difference depending on the vertical position of the blood vessel may affect the measurement results. For example, when measuring FFR, the left anterior descending coronary artery (LAD), located in the front of the heart, may be measured as if a pressure loss occurred due to the hydrostatic pressure difference even though there was no pressure loss in the blood flow because the pressure sensor is located higher than the entrance of the blood vessel. In addition, the left circumflex coronary artery (LCX) or the right coronary artery (RCA)

[0005] In some sections of the coronary artery (CA), the opposite phenomenon may occur. That is, the problem of overestimating FFR may occur in the LAD, and the problem of underestimating FFR may occur in some sections of the LCX or RCA. Accordingly, the development of a technology that compensates for the pressure difference in blood vessels due to differences in blood vessel height is required.

[0006] The present disclosure provides a method and an electronic device for correcting a pressure difference value of a blood vessel to solve the above-described problem.

[0007] The present disclosure can be implemented in various ways, including methods, devices (systems), and / or computer programs stored on a computer-readable storage medium.

[0008] According to one embodiment of the present disclosure, a method for correcting a pressure difference value of a blood vessel, performed by at least one processor, may include the steps of: obtaining at least one image of a blood vessel of a subject using a photographing device and photographing information of the photographing device for the at least one image; obtaining height information of a gravity direction of a blood vessel included in the at least one image based on the photographing information; calculating a difference value in height between a first point and a second point of the blood vessel based on the height information; calculating a difference value in pressure due to gravity between the first point and the second point of the blood vessel based on the difference value in height; and correcting a difference value in pressure due to gravity between the first point and the second point of the blood vessel based on the difference value in pressure.

[0009] According to one embodiment, the shooting information may include at least one of first distance information between an X-ray generating device included in the shooting device and an image acquisition device included in the shooting device, second distance information between the X-ray generating device and the subject to be examined, position information of the examination table, pixel spacing information of the image acquisition device, or angle information of the image acquisition device with respect to the subject to be examined.

[0010] According to one embodiment, the step of obtaining height information may include a step of obtaining calibration information and shooting direction information based on shooting information, a step of detecting a centerline of a blood vessel included in at least one image, a step of converting the centerline into three-dimensional coordinates based on the calibration information, and a step of obtaining height information in the gravity direction of the blood vessel based on the three-dimensional coordinates of the centerline.

[0011] According to one embodiment, the step of converting the center line into three-dimensional coordinates may include the step of converting image coordinates in which the center line is expressed into camera coordinates using internal parameters included in the calibration information, wherein the internal parameters include a matrix generated based on first distance information and pixel spacing information; the step of converting the camera coordinates into world coordinates using external parameters included in the calibration information, wherein the external parameters include a rotation matrix generated based on angle information and a transition vector indicating a camera position determined based on the rotation matrix and second distance information; and the step of moving the world coordinates into coordinates based on a rotation center of the photographing device using the second distance information and position information of the X-ray generating device.

[0012] According to one embodiment, at least one image includes a plurality of images of a blood vessel of a subject taken from different directions using a photographing device, and the step of obtaining height information may include a step of obtaining calibration information and photographing direction information based on photographing information of the photographing device for each of the plurality of images, a step of detecting a centerline of a blood vessel included in each of the plurality of images, a step of reconstructing the centerline of the blood vessel included in each of the plurality of images into a three-dimensional centerline based on the calibration information and the photographing information, and a step of obtaining height information of a gravity direction of the blood vessel based on coordinates of the three-dimensional centerline.

[0013] According to one embodiment, the step of reconstructing a centerline of a blood vessel included in each of a plurality of images into a three-dimensional centerline may include a step of identifying an epipolar line in a second image captured from a second direction of the photographing device among the plurality of images based on a first centerline of the blood vessel detected in a first image captured from a first direction of the photographing device among the plurality of images, a step of identifying a common point of the first centerline and the second centerline based on the second centerline and the epipolar line of the blood vessel detected in the second image, and a step of generating a three-dimensional centerline through triangulation based on the common point.

[0014] According to one embodiment, the step of calculating the pressure difference value may include the step of calculating the pressure difference value due to gravity between the first point and the second point of the blood vessel by multiplying the height difference value by the blood density of the blood vessel and the gravitational acceleration.

[0015] According to one embodiment, a method for correcting a pressure difference value of a blood vessel may further include a step of calculating information related to blood flow characteristics based on the corrected pressure difference value.

[0016] In one embodiment, the information related to the blood flow characteristics may include fractional blood flow reserve.

[0017] A computer program stored in a computer-readable recording medium may be provided to execute a method according to one embodiment of the present disclosure on a computer.

[0018] According to one embodiment of the present disclosure, an electronic device includes a memory and at least one processor connected to the memory and configured to execute at least one computer-readable program included in the memory, wherein the at least one program may include instructions for obtaining at least one image of a blood vessel of a subject by using a photographing device and photographing information of the photographing device for the at least one image, obtaining height information of a gravity direction of a blood vessel included in the at least one image based on the photographing information, calculating a difference value in height between a first point and a second point of the blood vessel based on the height information, calculating a difference value in pressure due to gravity between the first point and the second point of the blood vessel based on the difference value in height, and correcting a difference value in pressure due to gravity between the first point and the second point of the blood vessel based on the difference value in pressure.

[0019] According to some embodiments of the present disclosure, more accurate FFR measurement can be supported by correcting the pressure difference value of a blood vessel according to the difference in the height of the blood vessel.

[0020] The effects of the present disclosure are not limited to the effects mentioned above, and other effects not mentioned can be clearly understood by a person having ordinary knowledge in the technical field to which the present disclosure belongs (referred to as “one skilled in the art”) from the description of the claims.

[0021] Embodiments of the present disclosure will be described below with reference to the accompanying drawings, wherein like reference numerals represent similar elements, but are not limited thereto.

[0022] FIG. 1 is a drawing exemplarily showing an electronic device for correcting a pressure difference value of a blood vessel according to one embodiment of the present disclosure.

[0023] FIG. 2 is a drawing for explaining the configuration of an electronic device according to one embodiment of the present disclosure.

[0024] FIG. 3 is a drawing for explaining the configuration of a processor of an electronic device according to one embodiment of the present disclosure.

[0025] FIG. 4 is a drawing showing a photographing device for photographing a vascular image according to one embodiment of the present disclosure.

[0026] FIG. 5 is a drawing for explaining angle information of an image acquisition device for a test object according to one embodiment of the present disclosure.

[0027] FIG. 6 is a drawing for explaining shooting information according to the positional relationship between the shooting device and the subject according to one embodiment of the present disclosure.

[0028] FIG. 7 is a diagram for explaining a method for obtaining height information in the direction of gravity of a blood vessel in a blood vessel image according to one embodiment of the present disclosure.

[0029] FIG. 8 is a diagram for explaining a method for obtaining height information in the direction of gravity of a blood vessel in multiple blood vessel images according to one embodiment of the present disclosure.

[0030] FIG. 9 is a drawing for explaining FFR in a blood vessel in which the location of the pressure sensor according to one embodiment of the present disclosure is located higher than the entrance to the blood vessel.

[0031] FIG. 10 is a drawing for explaining FFR in a blood vessel in which the position of the pressure sensor according to one embodiment of the present disclosure is located lower than the blood vessel entrance.

[0032] FIG. 11 is a drawing for explaining a method for correcting a pressure difference value of a blood vessel according to one embodiment of the present disclosure.

[0033] FIG. 12 is a diagram illustrating an artificial neural network model according to one embodiment of the present disclosure.

[0034] Hereinafter, specific details for implementing the present disclosure will be described in detail with reference to the attached drawings. However, in the following description, specific descriptions of widely known functions or configurations will be omitted if they may unnecessarily obscure the gist of the present disclosure.

[0035] In the attached drawings, identical or corresponding components are assigned the same reference numerals. Furthermore, in the description of the embodiments below, duplicate descriptions of identical or corresponding components may be omitted. However, even if a description of a component is omitted, it is not intended that such component is not included in any embodiment.

[0036] The advantages and features of the disclosed embodiments, and methods for achieving them, will become clearer with reference to the embodiments described below, along with the accompanying drawings. However, the present disclosure is not limited to the embodiments disclosed below and may be implemented in various different forms. These embodiments are provided solely to ensure the completeness of the disclosure and to fully inform those skilled in the art of the scope of the invention.

[0037] The terms used in this specification will be briefly explained, followed by a detailed description of the disclosed embodiments. The terms used in this specification have been selected from widely used, current terms, taking into account the functions of the present disclosure. However, these terms may vary depending on the intentions of engineers working in the relevant field, precedents, the emergence of new technologies, etc. Furthermore, in certain cases, terms may be arbitrarily selected by the applicant, and in such cases, their meanings will be described in detail in the relevant description of the invention. Therefore, the terms used in this disclosure should not be defined simply as names of terms, but rather based on their meanings and the overall content of the present disclosure.

[0038] In this specification, singular expressions include plural expressions unless the context clearly indicates otherwise. Furthermore, plural expressions include singular expressions unless the context clearly indicates otherwise. When a part of the specification is said to include a component, this does not exclude other components, but rather implies that other components may be included, unless otherwise specifically stated.

[0039] Also, the term 'module' or 'part' used in the specification means a software or hardware component, and the 'module' or 'part' performs certain roles. However, the 'module' or 'part' is not limited to software or hardware. The 'module' or 'part' may be configured to reside on an addressable storage medium and may be configured to execute one or more processors. Thus, as an example, the 'module' or 'part' may include at least one of components such as software components, object-oriented software components, class components, and task components, processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays, or variables. The functionality provided within the components and 'modules' or 'parts' may be combined into a smaller number of components and 'modules' or 'parts', or further separated into additional components and 'modules' or 'parts'.

[0040] According to one embodiment of the present disclosure, a 'module' or 'unit' may be implemented as a processor and a memory. 'Processor' should be broadly construed to include a general-purpose processor, a central processing unit (CPU), a microprocessor, a digital signal processor (DSP), a controller, a microcontroller, a state machine, and the like. In some circumstances, a 'processor' may also refer to an application-specific integrated circuit (ASIC), a programmable logic device (PLD), a field-programmable gate array (FPGA), and the like. A 'processor' may also refer to a combination of processing devices, such as, for example, a combination of a DSP and a microprocessor, a combination of multiple microprocessors, a combination of one or more microprocessors in conjunction with a DSP core, or any other such combination of configurations. In addition, 'memory' should be broadly construed to include any electronic component capable of storing electronic information. 'Memory' may refer to various types of processor-readable media, such as random access memory (RAM), read-only memory (ROM), non-volatile random access memory (NVRAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable PROM (EEPROM), flash memory, magnetic or optical data storage, registers, etc. Memory is said to be in electronic communication with the processor if the processor can read information from, and / or write information to, the memory. Memory integrated in a processor is in electronic communication with the processor.

[0041] In addition, terms such as first, second, A, B, (a), (b), etc. used in the following embodiments are only used to distinguish certain components from other components, and the nature, order, or sequence of the components are not limited by the terms.

[0042] Additionally, in the embodiments below, when it is described that a component is 'connected', 'coupled' or 'connected' to another component, it should be understood that the component may be directly connected or connected to the other component, but another component may also be 'connected', 'coupled' or 'connected' between each component.

[0043] Additionally, the words 'comprises' and / or 'comprising' used in the following embodiments do not exclude the presence or addition of one or more other components, steps, operations and / or elements.

[0044] Hereinafter, various embodiments of the present disclosure will be described in detail with reference to the attached drawings.

[0045] FIG. 1 is a diagram exemplarily showing an electronic device for correcting a pressure difference value of a blood vessel according to one embodiment of the present disclosure. Referring to FIG. 1, the electronic device (100) can correct a pressure difference value (140) of a blood vessel based on at least one blood vessel image (110) and photographing information (120) of an photographing device for at least one blood vessel image (110). Here, the blood vessel image (110) may refer to an image of a blood vessel of a subject (e.g., a patient) taken using a photographing device for the purpose of diagnosing, treating, preventing, etc. a disease. In addition, the blood vessels included in the blood vessel image (110) may include coronary arteries or cerebral blood vessels. Coronary arteries are located in a form that surrounds the heart in a coronal shape, and can be classified into detailed types based on the position of placement. For example, the coronary arteries can be divided into the right coronary artery (RCA), which originates from the right side of the ascending aorta and runs mainly to the right side of the heart, and the left coronary artery (LCA), which originates from the left side of the ascending aorta and runs mainly to the left side of the heart. In addition, the left coronary artery can be further divided into the left main coronary artery (LMCA) (hereinafter referred to as LM) which originates from the upper left side of the heart, the left anterior descending coronary artery (LAD) which branches off from the left main coronary artery, and the left circumflex coronary artery (LCX). The cerebral blood vessels are located in a form that runs from the aortic arch toward the head, and can be further divided into types based on their location.For example, the common carotid artery (CCA) branches into the internal carotid artery (ICA) and the external carotid artery (ECA), and the vertebral artery (VA, aortic arch) branches from the subclavian artery. The left and right internal carotid arteries and the left and right vertebral arteries, a total of four blood vessels, are the main blood vessels supplying blood to the brain. The four blood vessels may be connected to each other by the anterior communicating artery (ACoA) and the left and right posterior communicating arteries (PCoA), and since they form a single ring, this is referred to as the circle of Willis. According to one embodiment, the vascular image (110) may include an image captured through coronary angiography (CAG). For example, the vascular image (110) may include an image of the coronary artery of the subject taken using a photographing device (e.g., a Carm X-ray photographing device) while a contrast agent is injected into the blood vessel of the subject. In addition, the photographing information (120) of the photographing device for the vascular image (110) is the photographing information (120) of the photographing device at the time of taking the vascular image (110), and may include, for example, at least one of distance information between an X-ray generating device included in the photographing device and an image acquisition device included in the photographing device, distance information between the X-ray generating device and the subject, position information of an examination table, pixel spacing information of the image acquisition device, or angle information of the image acquisition device with respect to the subject. The photographing information (120) of the photographing device for the vascular image (110) will be described in detail with reference to FIGS. 5 and 6.

[0046] Although a storage system capable of communicating with the electronic device (100) is not illustrated in FIG. 1, the electronic device (100) may be configured to be connected to or communicate with one or more storage systems. The storage system configured to be connected to or communicate with the electronic device (100) may include a device or cloud system that stores and manages various data related to the task of correcting the pressure difference value (140) of the blood vessel using the blood vessel image (110) and the photographing information (120) of the photographing device for the blood vessel image (110). For efficient data management, the storage system may store and manage various data using a database. Here, the various data may include any data related to the task of correcting the pressure difference value (140) of the blood vessel using the blood vessel image (110) and the photographing information (120) of the photographing device for the blood vessel image (110). For example, various data may include, but are not limited to, a machine learning model, learning data, a vascular image (110), and shooting information (120) related to the task of correcting a pressure difference value (140) of a blood vessel using a vascular image (110) and shooting information (120) of a shooting device for the vascular image (110).

[0047] According to one embodiment, after the blood vessels of a subject are photographed by a photographing device, the blood vessel image (110) of the photographed blood vessels may be input to an electronic device (100). For example, the electronic device (100) may be connected to the photographing device via wired or wireless communication, and the blood vessel image (110) may be provided from the photographing device to the electronic device (100) via a communication module. In some embodiments, the electronic device (100) may be provided as an integral part of the photographing device. As another example, the electronic device (100) may receive the blood vessel image (110) from an external electronic device (e.g., an external storage device) connected via a communication module. The method by which the electronic device (100) acquires the blood vessel image (110) is not limited to the above-described example, and any method may be used.

[0048] According to one embodiment, the photographing information (120) of the photographing device for the blood vessel image (110) may be input to the electronic device (100) together with the blood vessel image (110) or at a predetermined time interval. For example, when the electronic device (100) is connected to the photographing device through wired or wireless communication, the photographing device may obtain the photographing information (120) of the photographing device at the time when the blood vessel image (110) is taken, and may provide the photographing information (120) obtained together with the blood vessel image (110) to the electronic device (100) through a communication module. As another example, when the electronic device (100) is provided as an integral part with the photographing device, the electronic device (100) may obtain the photographing information (120) of the photographing device together with the blood vessel image (110) at the time when the photographing device takes the blood vessel image (110). As another example, the electronic device (100) can receive imaging information (120) together with a vascular image (110) from an external electronic device (e.g., an external storage device) connected via a communication module.

[0049] A process of correcting a pressure difference value (140) of a blood vessel based on a blood vessel image (110) and photographing information (120) of an photographing device for the blood vessel image (110) will be described. First, the electronic device (100) may obtain at least one blood vessel image (110) and photographing information (120) of an photographing device for the at least one blood vessel image (110). For example, the electronic device (100) may receive at least one blood vessel image (110) and photographing information (120) of an photographing device for the at least one blood vessel image (110) through a communicable storage medium (e.g., a hospital system, a local / cloud storage system, etc.).

[0050] Then, the electronic device (100) can obtain height information in the direction of gravity of a blood vessel included in at least one blood vessel image (110) based on the shooting information (120). According to one embodiment, the electronic device (100) can obtain calibration information and shooting direction information based on the shooting information (120), detect a centerline of a blood vessel included in at least one blood vessel image (110), convert the centerline into a three-dimensional coordinate based on the calibration information, and obtain height information in the direction of gravity of the blood vessel based on the three-dimensional coordinate of the centerline. Here, in order to convert the center line into a three-dimensional coordinate, the electronic device (100) converts the image coordinates in which the center line is expressed into camera coordinates using an intrinsic parameter included in the calibration information, wherein the intrinsic parameter includes a matrix generated based on distance information between the X-ray generating device and the image acquisition device and pixel spacing information of the image acquisition device, and converts the camera coordinates into world coordinates using an extrinsic parameter included in the calibration information, wherein the extrinsic parameter includes a rotation matrix generated based on angle information of the image acquisition device with respect to the subject to be examined and a transition vector indicating the camera position determined based on the rotation matrix and distance information between the X-ray generating device and the subject to be examined, and using the distance information between the X-ray generating device and the position information of the X-ray generating device, the world coordinates can be moved to coordinates based on the rotation center of the photographing device.

[0051] According to one embodiment, if at least one blood vessel image (110) includes a plurality of blood vessel images (110) in which blood vessels of a subject are captured from different directions using a photographing device, the electronic device (100) may obtain calibration information and photographing direction information based on photographing information (120) of the photographing device for each of the plurality of blood vessel images (110), detect a centerline of a blood vessel included in each of the plurality of blood vessel images (110), reconstruct the centerline of a blood vessel included in each of the plurality of blood vessel images (110) into a three-dimensional centerline based on the calibration information and the photographing information (120), and obtain height information in the direction of gravity of the blood vessel based on coordinates of the three-dimensional centerline. Here, in order to reconstruct the centerline of the blood vessel included in each of the plurality of blood vessel images (110) into a three-dimensional centerline, the electronic device (100) may identify an epipolar line in a second image captured from a second direction of the photographing device among the plurality of blood vessel images (110) based on a first centerline of the blood vessel detected in a first image captured from a first direction of the photographing device among the plurality of blood vessel images (110), identify a common point (e.g., CIP (Common Image Point)) of the first centerline and the second centerline based on the second centerline and the epipolar line of the blood vessel detected in the second image, and generate a three-dimensional centerline through triangulation based on the common point.

[0052] Then, the electronic device (100) can calculate a difference value in height between the first point and the second point of the blood vessel based on the height information.

[0053] Then, the electronic device (100) can calculate a difference value (130) of pressure due to gravity (e.g., hydrostatic pressure) between the first point and the second point of the blood vessel based on the difference value in height. For example, the electronic device (100) can calculate a difference value (130) of pressure due to gravity between the first point and the second point of the blood vessel by multiplying the blood density and gravitational acceleration of the blood vessel by the difference value in height.

[0054] Then, the electronic device (100) can correct the pressure difference value (140) between the first point and the second point of the blood vessel based on the pressure difference value (130) due to gravity. For example, the electronic device (100) can calculate the pressure difference value (140) between the first point and the second point of the blood vessel by adding the pressure difference value (130) due to gravity to the pressure difference value due to the narrowing of the inner diameter of the lesion. Here, the pressure difference value due to the narrowing of the inner diameter of the lesion may be a value measured using an FFR device.

[0055] FIG. 2 is a diagram illustrating a configuration of an electronic device according to an embodiment of the present disclosure. Referring to FIG. 2, the electronic device (100) may include a memory (210), a processor (220), a communication module (230), and an input / output interface (240). However, the configuration of the electronic device (100) is not limited thereto. According to various embodiments, the electronic device (100) may omit at least one of the above-described components and may further include at least one other component. As an example, the electronic device (100) may further include a display. In this case, the electronic device (100) may display a blood vessel image (e.g., a blood vessel image (110) of FIG. 1) captured by a blood vessel on the display.

[0056] The memory (210) can store various data used by at least one other component of the electronic device (100), for example, the processor (220). The data can include, for example, input data or output data for software (or a program) and instructions related thereto.

[0057] The memory (210) may include any non-transitory computer-readable recording medium. According to one embodiment, the memory (210) may include a non-permanent mass storage device such as a disk drive, a solid state drive (SSD), flash memory, etc. As another example, a non-permanent mass storage device such as a ROM, an SSD, a flash memory, a disk drive, etc. may be included in the electronic device (100) as a separate permanent storage device distinct from the memory (210). In addition, the memory (210) may store an operating system and at least one program code (e.g., a command for correcting a pressure difference value of a blood vessel installed and operated in the electronic device (100). In FIG. 2, the memory (210) is illustrated as a single memory, but this is merely for convenience of explanation, and the memory (210) may include a plurality of memories and / or buffer memories.

[0058] The software components may be loaded from a computer-readable recording medium separate from the memory (210). This separate computer-readable recording medium may include a recording medium directly connectable to the electronic device (100), for example, a computer-readable recording medium such as a floppy drive, a disk, a tape, a DVD / CD-ROM drive, a memory card, etc. As another example, the software components may be loaded into the memory (210) through a communication module (230) other than a computer-readable recording medium. For example, at least one program may be loaded into the memory (210) based on a computer program (e.g., a program for transmitting data such as an vascular image taken of an angiogram, etc.) that is installed by files provided by developers or a file distribution system that distributes installation files of applications through the communication module (230).

[0059] The processor (220) may execute software (or a program) to control at least one other component (e.g., a hardware or software component) of the electronic device (100) connected to the processor (220) and perform various data processing or operations. According to one embodiment, as at least a part of the data processing or operations, the processor (220) may load a command or data received from another component (e.g., a communication module (230)) into a volatile memory, process the command or data stored in the volatile memory, and store the resulting data in a non-volatile memory.

[0060] The processor (220) may be configured to process commands of a computer program by performing basic arithmetic, logic, and input / output operations. The commands may be provided to the electronic device (100) or another external system via the memory (210) or the communication module (230). For example, the processor (220) may correct the pressure difference value of a blood vessel using a blood vessel image and photographing information of a photographing device for the blood vessel image. Then, the processor (220) may store the corrected blood vessel pressure difference value in the memory (210), display it on the display of the electronic device (100), or transmit it to an external electronic device via the communication module (230). Alternatively, the processor (220) may perform additional analysis operations, such as calculating information related to blood flow characteristics, using the blood vessel pressure difference value. Here, the information related to blood flow characteristics may include fractional blood flow reserve. For example, the processor (220) may calculate the fractional blood flow reserve using the blood vessel pressure difference value. In FIG. 2, the processor (220) is depicted as a single processor, but this is only for convenience of explanation, and the processor (220) may include multiple processors.

[0061] The communication module (230) can support the establishment of a direct (e.g., wired) communication channel or wireless communication channel between the electronic device (100) and an external electronic device, and the performance of communication through the established communication channel. For example, the communication module (230) can provide a configuration or function for the electronic device (100) and an external electronic device (e.g., a user terminal or a cloud server) to communicate with each other via a network. For example, control signals, commands, data, etc. provided under the control of the processor (220) of the electronic device (100) can be transmitted to the external electronic device via the communication module (130) and the network through the communication module of the external electronic device. For example, the electronic device (100) can receive a blood vessel image obtained by photographing the blood vessels of a subject from an external electronic device via the communication module (230).

[0062] The input / output interface (240) may be a means for interfacing with a device (not shown) for input or output that may be connected to the electronic device (100) or that the electronic device (100) may include. For example, the input / output interface (240) may include at least one of a PCI express interface and an Ethernet interface. In FIG. 2, the input / output interface (240) is illustrated as an element configured separately from the processor (220), but is not limited thereto, and the input / output interface (240) may be configured to be included in the processor (220).

[0063] According to one embodiment, the processor (220) may perform a function related to correction of a pressure difference value of a blood vessel based on a blood vessel image and photographing information of an imaging device for the blood vessel image. The processor (220) may execute at least one computer-readable program included in the memory (210) to perform a function related to correction of a pressure difference value of a blood vessel. Here, the at least one program may include instructions for obtaining at least one image of a blood vessel of a subject captured using an imaging device and photographing information of the imaging device for the at least one image, obtaining height information of a gravity direction of a blood vessel included in the at least one image based on the photographing information, calculating a height difference value between a first point and a second point of the blood vessel based on the height information, calculating a pressure difference value due to gravity between the first point and the second point of the blood vessel based on the height difference value, and correcting a pressure difference value between the first point and the second point of the blood vessel based on the pressure difference value due to gravity. In the following description, for convenience of explanation, the processor (220) executing at least one program to perform a function related to correction of a pressure difference value of a blood vessel based on a blood vessel image and capturing information of an imaging device for the blood vessel image may be described as the processor (220) performing a function related to correction of a pressure difference value of a blood vessel based on a blood vessel image and capturing information of an imaging device for the blood vessel image. For example, the description that at least one program includes a command related to correction of a pressure difference value of a blood vessel based on a blood vessel image and capturing information of an imaging device for the blood vessel image may correspond to the description that the processor (220) performs a function related to correction of a pressure difference value of a blood vessel based on a blood vessel image and capturing information of an imaging device for the blood vessel image.

[0064] According to one embodiment, the processor (220) may correct the pressure difference value of a blood vessel through a machine learning model that inputs a blood vessel image and photographing information of an imaging device for the blood vessel image. Here, the machine learning model may include any model used to infer an answer for a given input. According to one embodiment, the machine learning model may include an artificial neural network model including an input layer (layer), multiple hidden layers, and an output layer. Here, each layer may include one or more nodes. In addition, the machine learning model may include weights associated with multiple nodes included in the machine learning model. Here, the weights may include any parameters associated with the machine learning model. The machine learning model of the present disclosure may be a model learned using various learning methods. For example, various learning methods such as supervised learning, semi-supervised learning, unsupervised learning (or unsupervised learning), and reinforcement learning may be used in the present disclosure. In this disclosure, a machine learning model may refer to an artificial neural network model, and an artificial neural network model may refer to a machine learning model. The artificial neural network model will be described in detail with reference to Figure 12.

[0065] FIG. 3 is a diagram for explaining the configuration of a processor of an electronic device according to one embodiment of the present disclosure. Referring to FIG. 3, the processor (220) may use a blood vessel image (e.g., a blood vessel image (110) of FIG. 1) and photographing information of a photographing device for the blood vessel image (e.g., photographing information (120) of FIG. 1) to calculate a difference value of pressure due to gravity between a first point and a second point of the blood vessel (e.g., a difference value of pressure due to gravity (130) of FIG. 1) and, based on the difference value of pressure due to gravity, correct a difference value of pressure between the first point and the second point of the blood vessel (e.g., a difference value of pressure of the blood vessel (140) of FIG. 1). To this end, the processor (220) may include an image acquisition module (310), a photographing information acquisition module (320), a height information acquisition module (330), a pressure difference calculation module (340), and a pressure difference correction module (350). However, the types of components included in the processor (220) are classified according to the function related to the correction of the difference value of blood vessel pressure using the photographing information of the photographing device for blood vessel images and blood vessel projections, and the types and number thereof are not limited thereto. In addition, at least one of the components included in the processor (220) may be implemented in the form of a command stored in a memory (e.g., the memory (210) of FIG. 2).

[0066] The image acquisition module (310) can acquire at least one blood vessel image that has captured a blood vessel. According to one embodiment, the image acquisition module (310) can acquire an image of a blood vessel of a subject by using an imaging device (e.g., a C-arm X-ray imaging device) while a contrast agent is injected into the blood vessel of the subject. For example, the blood vessel image may include an image captured through coronary angiography. Such a blood vessel image may be received from a storage system (e.g., a hospital system, an electronic medical record, a prescription delivery system, a medical imaging system, a test information system, a local / cloud storage system, etc.) connected to or capable of communication with the electronic device (100), an internal memory, and / or a user terminal.

[0067] The photographing information acquisition module (320) can acquire photographing information of a photographing device for at least one vascular image. Here, the photographing device may include, for example, a C-arm X-ray photographing device. In addition, the photographing information is photographing information of the photographing device at the time of photographing at least one vascular image, and may include, for example, at least one of distance information between an X-ray generating device included in the photographing device and an image acquisition device included in the photographing device, distance information between the X-ray generating device and the subject, position information of an examination table, pixel spacing information of the image acquisition device, or angle information of the image acquisition device with respect to the subject.

[0068] The height information acquisition module (330) can acquire height information in the direction of gravity of a blood vessel included in at least one blood vessel image based on the shooting information. When the number of blood vessel images used to acquire height information is one, a method of converting two-dimensional coordinates of the blood vessel image into three-dimensional coordinates can be used. In addition, when the number of blood vessel images used to acquire height information is multiple, a method of converting two-dimensional coordinates of the blood vessel image into three-dimensional coordinates or a method of reconstructing a three-dimensional shape of the blood vessel using multiple blood vessel images can be used.

[0069] With respect to a method for converting two-dimensional coordinates of a blood vessel image into three-dimensional coordinates, the height information acquisition module (330) can acquire calibration information and shooting direction information based on shooting information. Then, the height information acquisition module (330) can detect a centerline of a blood vessel included in at least one blood vessel image. Then, the height information acquisition module (330) can convert the centerline into three-dimensional coordinates based on the calibration information. For example, the height information acquisition module (330) can convert image coordinates in which the centerline is expressed into camera coordinates using internal parameters included in the calibration information. At this time, the internal parameters can include a matrix generated based on distance information between an X-ray generator and an image acquisition device and pixel interval information of the image acquisition device. In addition, the height information acquisition module (330) can convert camera coordinates into world coordinates using external parameters included in the calibration information. At this time, the external parameters may include a rotation matrix generated based on angle information of the image acquisition device for the subject and a transition vector indicating a camera position determined based on distance information between the rotation matrix and the X-ray generator and the subject. In addition, the height information acquisition module (330) may use distance information between the X-ray generator and the subject and position information of the X-ray generator to move the world coordinates to coordinates based on the rotation center of the photographing device. Then, the height information acquisition module (330) may acquire height information in the direction of gravity of the blood vessel based on the three-dimensional coordinates of the center line.

[0070] In relation to a method for reconstructing a three-dimensional shape of a blood vessel using multiple blood vessel images, at least one blood vessel image may include multiple blood vessel images taken from different directions of blood vessels of a subject using a photographing device. At this time, the height information acquisition module (330) may acquire calibration information and photographing direction information based on photographing information of the photographing device for each of the multiple blood vessel images. Then, the height information acquisition module (330) may detect a centerline of a blood vessel included in each of the multiple blood vessel images. Then, the height information acquisition module (330) may reconstruct the centerline of the blood vessel included in each of the multiple blood vessel images into a three-dimensional centerline based on the calibration information and the photographing information. For example, the height information acquisition module (330) may identify an epipolar line in a second image taken from a second direction of the photographing device among the multiple blood vessel images based on a first centerline of a blood vessel detected in a first image taken from a first direction of the photographing device among the multiple blood vessel images. Additionally, the height information acquisition module (330) can identify a common point between the first center line and the second center line based on the second center line and epipolar line of the blood vessel detected in the second image. Furthermore, the height information acquisition module (330) can generate a three-dimensional center line through triangulation based on the common point. Then, the height information acquisition module (330) can acquire height information in the gravity direction of the blood vessel based on the coordinates of the three-dimensional center line.

[0071] The height information acquisition module (330) can calculate a difference in height between two points of a blood vessel based on the acquisition of height information in the direction of gravity of the blood vessel. For example, the height information acquisition module (330) can calculate a difference in height between a first point and a second point of the blood vessel.

[0072] The pressure difference calculation module (340) can calculate the difference value of the pressure due to gravity (e.g., hydrostatic pressure) at two points of the blood vessel based on the difference value of the height at two points of the blood vessel. For example, the pressure difference calculation module (340) can calculate the difference value of the pressure due to gravity between the first point and the second point of the blood vessel by multiplying the difference value of the height between the first point and the second point of the blood vessel by the blood density and the acceleration of gravity of the blood vessel.

[0073] The pressure difference correction module (350) can correct the pressure difference between two points of the blood vessel based on the pressure difference due to gravity at the two points of the blood vessel. For example, the pressure difference correction module (350) can calculate the pressure difference between two points of the blood vessel (e.g., the first point and the second point) by adding the pressure difference due to the pressure narrowing of the lesion to the pressure difference due to gravity. Here, the pressure difference due to the pressure narrowing of the lesion may be a value measured using an FFR device.

[0074] FIG. 4 is a diagram illustrating an imaging device for capturing blood vessel images according to one embodiment of the present disclosure. Referring to FIG. 4, the imaging device (400) can capture images of blood vessels of a subject. For example, the imaging device (400) can capture images of blood vessels of a subject while a contrast agent is injected into the blood vessels of the subject. According to one embodiment, the imaging device (400) may include a C-arm X-ray imaging device.

[0075] The photographing device (400) may include a main body (410), an elevator unit (420), a rotation unit (430), a C-shaped frame unit (440), an X-ray generation unit (454), and an image acquisition device (452). However, the configuration of the photographing device (400) is not limited thereto. The photographing device (400) may be provided in any configuration and in any form as long as it includes an image acquisition device (452).

[0076] The main body (410) may have a built-in driving unit for lifting. According to one embodiment, the main body (410) may have a built-in control unit (e.g., a processor) for controlling the configuration of the photographing device (400). In addition, when the photographing device (400) is connected to the electronic device (100) of FIGS. 1 and 2 via a communication module, the main body (410) may have a built-in communication module.

[0077] The elevating member (420) is fixed to the upper end of the elevating driving member built into the main body (410) and can be elevated in a first direction (492) (e.g., up and down). For example, the elevating member (420) can be adjusted to the height of the examination subject (or photographing subject) (e.g., the heart) depending on the posture of the examination subject.

[0078] The rotating part (430) is connected to the lifting part (420) so as to be rotatable (494) around a first axis in a second direction that is perpendicular to the first direction (492), and a curved surface may be formed at the other end. When the rotating part (430) rotates (494) around the first axis, the rotation angle (e.g., the first rotation angle) of the image acquisition device (452) may be changed. Here, the first axis may be an axis in the up-and-down direction (or the longitudinal direction) of the subject (e.g., the direction connecting the head and the feet) or an axis parallel thereto. For example, the rotation (494) of the rotating part (430) around the first axis may indicate that the image acquisition device (452) rotates around the first axis, and the rotation of the image acquisition device (452) around the first axis may indicate that the image acquisition device (452) rotates left-right around the torso (or heart) of the subject. In the following description, the rotation angle information of the image acquisition device (452) formed when the rotation part (430) rotates (494) around the first axis may be referred to as first rotation angle information.

[0079] The C-shaped frame part (440) is slidably connected (496) to the curved surface formed on the rotating part (430) and may be provided in a C shape (or a ring shape with a portion cut off). Due to the shape of the C-shaped frame part (440), the photographing device (400) may be referred to as a C-arm or a C-arm photographing device. When the C-shaped frame part (440) slides (496) on the curved surface formed on the rotating part (430), the rotation angle (e.g., the second rotation angle) of the image acquisition device (452) may be changed. When the C-shaped frame part (440) slides (496) on the curved surface formed on the rotating part (430), the image acquisition device (452) may rotate around a second axis in a third direction perpendicular to the first direction (492) and the second direction. Here, the second axis may be an axis in the left-right direction (or width direction) of the subject (e.g., the direction connecting both shoulders or both arms) or an axis parallel thereto. For example, when the C-shaped frame part (440) slides (496) on the curved surface formed on the rotation part (430), it indicates that the image acquisition device (452) rotates around the second axis, and when the image acquisition device (452) rotates around the second axis, it may indicate that the image acquisition device (452) rotates up and down around the torso (or heart) of the subject. In the following description, the rotation angle information of the image acquisition device (452) formed when the C-shaped frame part (440) slides (496) on the curved surface formed on the rotation part (430) may be referred to as second rotation angle information.

[0080] An X-ray generating device (454) may be arranged at one end of a C-shaped frame portion (440), and an image acquisition device (452) may be arranged at the other end of the C-shaped frame portion (440). The X-ray generating device (454) may generate X-rays and transmit them to an examination subject (or a photographing subject), and the amount of X-rays transmitted may be detected by the image acquisition device (452), and the image may be signal-processed to obtain an image (e.g., a blood vessel image (110) of FIG. 1). At this time, the photographing device (400) may obtain photographing information (e.g., photographing information (120) of FIG. 1) of the photographing device (400) at the time of photographing the image together with the image obtained through the image acquisition device (452). The shooting information may include, for example, at least one of distance information between the X-ray generator (454) and the image acquisition device (452), distance information between the X-ray generator (454) and the subject, position information of the examination table, pixel spacing information of the image acquisition device (452), or angle information of the image acquisition device (452) with respect to the subject (e.g., first rotation angle information and second rotation angle information).

[0081] FIG. 5 is a drawing for explaining angle information of an image acquisition device for a test subject according to one embodiment of the present disclosure. Referring to FIG. 5, the photographing device (400) can change (or set) the angles (522, 524) of the image acquisition device (452) to correspond to a blood vessel area to be photographed in order to determine in which area an abnormality has occurred in relation to the blood vessels of the test subject. As described with reference to FIG. 4, the photographing device (400) has an X-ray generation device (454) and an image acquisition device (452) arranged at both ends of a C-shaped frame part (440), and the angles (522, 524) of the image acquisition device (452) can be changed by sliding the C-shaped frame part (440) on a curved surface of a rotating part (e.g., sliding (496) in FIG. 4) or rotating the rotating part (e.g., rotating (494) in FIG. 4)).

[0082] The angle (522, 524) of the image acquisition device (452) can be set based on the examination subject (or shooting subject). For example, when the examination subject lies down on the examination table (510), the up-down direction (or length direction) of the examination subject (e.g., the direction connecting the head and the feet) may be the X-axis direction, and the left-right direction (or width direction) of the examination subject (e.g., the direction connecting both shoulders or both arms) may be the Y-axis direction. Here, more specifically, the direction from the head to the feet may be the (+) X-axis direction, conversely, the direction from the feet to the head may be the (-) X-axis direction, the direction from the right shoulder (or right arm) to the left shoulder (or left arm) may be the (+) Y-axis direction, and the direction from the left shoulder (or left arm) to the right shoulder (or right arm) may be the (-) Y-axis direction. At this time, the first rotation angle information of the image acquisition device (452) formed when the rotating part rotates and the image acquisition device (452) rotates around the X-axis may be set to the first rotation angle (α) (522), and the second rotation angle information of the image acquisition device (452) formed when the C-shaped frame part (440) slides on the curved surface of the rotating part and the image acquisition device (452) rotates around the Y-axis may be set to the second rotation angle (β) (524).

[0083] The first rotation angle (522) may be referred to as a primary angle. When the first rotation angle (522) has a rotation angle in the (-) Y-axis direction, the image may be referred to as having a RAO view, and the first rotation angle (522) may be expressed as an RAO angle. In addition, when the first rotation angle (522) has a rotation angle in the (+) Y-axis direction, the image may be referred to as having a LAO view, and the first rotation angle (522) may be expressed as an LAO angle. In addition, when the first rotation angle (522) has a rotation angle about the Y-axis (i.e., 0 degrees), the image may be referred to as having an AP view.

[0084] The second rotation angle (524) may be referred to as a secondary angle. When the second rotation angle (524) has a rotation angle in the (-) X-axis direction, the image may be referred to as having a CRA (or CRANIAL) view, and the second rotation angle (524) may be expressed as a CRA angle. Additionally, when the second rotation angle (524) has a rotation angle in the (+) X-axis direction, the image may be referred to as having a CAU (or CAUDAL) view, and the second rotation angle (524) may be expressed as a CAU angle.

[0085] According to one embodiment, the type of blood vessel to be identified or included in the image can be set through a combination of the first rotation angle (522) and the second rotation angle (524).

[0086] FIG. 6 is a diagram for explaining photographing information according to the positional relationship between the photographing device and the subject according to one embodiment of the present disclosure. Referring to FIG. 6, a processor (e.g., a processor (220) of FIGS. 2 and 3) of an electronic device (e.g., an electronic device (100) of FIGS. 1 and 2) for correcting a pressure difference value of a blood vessel can obtain photographing information (e.g., photographing information (120) of FIG. 1) of an photographing device (400) for at least one blood vessel image (e.g., a blood vessel image (110) of FIG. 1) taken of a blood vessel. The shooting information may include at least one of distance information (SID, Source to Image receptor Distance) between the X-ray generator (454) and the image acquisition device (452), distance information (SOD, Source to Object Distance) between the X-ray generator (454) and the subject (610) (or the subject (612) (e.g., heart)), position information of the examination table (510), pixel spacing information of the image acquisition device (452), or angle information (e.g., first rotation angle information and second rotation angle information) of the image acquisition device (452) with respect to the subject (610).

[0087] According to one embodiment, the processor can calculate distance information between the X-ray generator (454) and the subject (610) through the following 1.

[0088] [Mathematical Formula 1]

[0089]

[0090] Here, SOD represents distance information between the X-ray generator (454) and the subject (610) (or the subject (612) (e.g., heart)), ISO represents distance information between the X-ray generator (454) and the rotation center (620) of the photographing device (400), TH represents distance information between the examination table (510) and the rotation center (620) of the photographing device (400), and TO may represent distance information between the examination table (510) and the subject (610) (or the subject (612) (e.g., heart)).

[0091] According to one embodiment, the processor may obtain a direction vector from the X-ray generator (454) to coordinates representing the subject (610) (or the subject (612) (e.g., the heart)) using the following mathematical expression 2.

[0092] [Equation 2]

[0093]

[0094] Here, D represents a direction vector from the X-ray generator (454) to the coordinates indicating the subject (610) (or the subject (612) (e.g., the heart)), #Px represents the number of pixels of the image acquisition device (452), ΔPx represents pixel spacing information of the image acquisition device (452), SOD represents distance information between the X-ray generator (454) and the subject (610) (or the subject (612) (e.g., the heart)), and SID may represent distance information between the X-ray generator (454) and the image acquisition device (452).

[0095] FIG. 7 is a diagram for explaining a method for obtaining height information in the direction of gravity of a blood vessel in a blood vessel image according to one embodiment of the present disclosure. Referring to FIG. 7, a processor (e.g., a processor (220) in FIGS. 2 and 3) of an electronic device (e.g., an electronic device (100) in FIGS. 1 and 2) for correcting a pressure difference value of a blood vessel may obtain height information in the direction of gravity of a blood vessel included in at least one blood vessel image (710) based on shooting information (e.g., shooting information (120) in FIG. 1) of a shooting device (e.g., a shooting device (400) in FIG. 4) for at least one blood vessel image (710) (e.g., a blood vessel image (110) in FIG. 1).

[0096] The processor can obtain calibration information and shooting direction information based on the shooting information. Then, the processor can detect the centerline (712) of the blood vessel included in at least one blood vessel image (710). Then, the processor can convert the centerline (712) of the blood vessel into a centerline (714) of the blood vessel having three-dimensional coordinates based on the calibration information. For example, the processor can convert the image coordinates in which the centerline (712) of the blood vessel is expressed into camera coordinates using internal parameters included in the calibration information. At this time, the internal parameters can include a matrix generated based on distance information between an X-ray generator (e.g., an X-ray generator (454) of FIGS. 4 to 6) and an image acquisition device (e.g., an image acquisition device (452) of FIGS. 4 to 6) and pixel interval information of the image acquisition device. In addition, the processor can convert the camera coordinates into world coordinates using external parameters included in the calibration information. At this time, the external parameters may include a rotation matrix generated based on angle information of an image acquisition device for a subject (e.g., a subject (610) of FIG. 4) and a transition vector indicating a camera position determined based on distance information between the rotation matrix and the X-ray generating device and the subject.

[0097] According to one embodiment, the processor can convert the centerline (712) of a blood vessel having two-dimensional coordinates included in a blood vessel image (710) into the centerline (714) of a blood vessel having three-dimensional coordinates through the following mathematical equations 3, 4, and 5.

[0098] [Equation 3]

[0099]

[0100] [Equation 4]

[0101]

[0102] [Equation 5]

[0103]

[0104] Here, (X, Y, Z) represent three-dimensional coordinates of the blood vessel centerline (714), (x, y) represent two-dimensional coordinates of the blood vessel centerline (712), K represents an internal parameter, R represents a rotation matrix generated based on angle information of the image acquisition device with respect to the subject, T represents a transition vector indicating a camera position determined based on R and SOD, SOD represents distance information between the X-ray generator and the subject (or inspection target), SID represents distance information between the X-ray generator and the image acquisition device, and IPS may represent pixel spacing information of the image acquisition device.

[0105] Then, the processor can use the distance information between the X-ray generator and the subject and the position information of the X-ray generator to move the world coordinates to coordinates based on the rotation center of the photographing device (e.g., the rotation center (620) of the photographing device in FIG. 6). Then, the processor can obtain height information in the direction of gravity of the blood vessel based on the three-dimensional coordinates of the center line (714) of the blood vessel.

[0106] According to one embodiment, the processor can move the world coordinates, i.e., the three-dimensional coordinates of the blood vessel centerline (714), to coordinates based on the rotation center of the photographing device through the following mathematical expression 6.

[0107] [Equation 6]

[0108]

[0109] Here, X iso represents the coordinates based on the rotation center of the shooting device, and X img represents the three-dimensional coordinates of the blood vessel centerline (714), and C pos represents the location information of the X-ray generator, SOD represents the distance information between the X-ray generator and the subject to be examined, and D can represent the direction vector from the X-ray generator to the coordinate representing the subject to be examined.

[0110] FIG. 8 is a diagram for explaining a method for obtaining height information in the direction of gravity of a blood vessel from a plurality of blood vessel images according to one embodiment of the present disclosure. Referring to FIG. 8, a processor (e.g., a processor (220) in FIGS. 2 and 3) of an electronic device (e.g., an electronic device (100) in FIGS. 1 and 2) for correcting a pressure difference value of a blood vessel can obtain height information in the direction of gravity of a blood vessel included in a plurality of blood vessel images (810, 820) based on shooting information (e.g., shooting information (120) in FIG. 1) of a shooting device (e.g., a shooting device (400) in FIG. 4) for each of a plurality of blood vessel images (810, 820) (e.g., a blood vessel image (110) in FIG. 1).

[0111] The processor can obtain calibration information and shooting direction information based on the shooting information. Then, the processor can detect the centerline (812, 822) of the blood vessel included in each of the plurality of blood vessel images (810, 820). Then, the processor can reconstruct the centerline (812, 822) of the blood vessel included in each of the plurality of blood vessel images (810, 820) into a three-dimensional centerline (830) based on the calibration information and the shooting information. For example, the processor can identify an epipolar line in a second image (820) captured in a second direction of the shooting device among the plurality of blood vessel images (810, 820), based on the first centerline (812) of the blood vessel detected in a first image (810) captured in a first direction of the shooting device among the plurality of blood vessel images (810, 820). Additionally, the processor may identify a common point of the first centerline (812) and the second centerline (822) based on the second centerline (822) and the epipolar line of the blood vessel detected in the second image (820). Here, the epipolar line (or epiline) is a line where an epipolar plane intersects an image plane (e.g., the first image (810) and the second image (820)), and when a point is given in one image plane (e.g., the first image (810)), the corresponding point of the point may necessarily be located on the epipolar line of another image plane (e.g., the second image (820)). That is, the processor can extract at least one feature point (or common point) by using geometric three-dimensional information through a first position of the photographing device associated with capturing the first image (810), a second position of the photographing device associated with capturing the second image (820), and an epipolar plane passing through a point of the blood vessel. In addition, the processor can generate a three-dimensional centerline (830) through triangulation based on the common point. Then, the processor can obtain height information in the direction of gravity of the blood vessel based on the coordinates of the three-dimensional centerline (830).

[0112] FIG. 9 is a diagram for explaining FFR in a blood vessel in which the position of the pressure sensor is positioned higher than the blood vessel entrance according to one embodiment of the present disclosure, and FIG. 10 is a diagram for explaining FFR in a blood vessel in which the position of the pressure sensor is positioned lower than the blood vessel entrance according to one embodiment of the present disclosure. Referring to FIGS. 9 and 10 , blood flow characteristic values ​​such as FFR can be used for diagnosis in order to quickly and accurately diagnose vascular lesions such as coronary artery stenosis. FFR can be calculated by measuring the pressure difference between two points of the blood vessel (e.g., proximal and distal). At this time, in addition to the pressure loss due to the narrowing of the inner diameter of the lesion, the pressure difference (e.g., hydrostatic pressure) depending on the vertical position of the blood vessel can affect the measurement result. For example, when measuring FFR, the pressure difference value due to gravity depending on the position of the pressure sensor, i.e., the height difference of the blood vessel, can affect the pressure difference value of the blood vessel. Accordingly, more accurate FFR measurement can be supported by correcting the pressure difference value of the blood vessel based on the pressure difference value due to gravity according to the difference in the height of the blood vessel.

[0113] In Fig. 9, the FFR in a blood vessel, for example, the LAD, is shown, where the pressure sensor is positioned higher than the blood vessel entrance. 910 of Fig. 9 represents the FFR using the pressure difference value of the blood vessel excluding the pressure difference value due to gravity according to the height difference of the blood vessel, and 920 of Fig. 9 may represent the FFR using the pressure difference value of the blood vessel corrected based on the pressure difference value due to gravity according to the height difference of the blood vessel. In the LAD, the pressure sensor is positioned higher than the blood vessel entrance, so that even if there is no pressure loss in the blood flow, it may be measured as if a pressure loss occurred due to the hydrostatic pressure difference. Accordingly, the problem of overestimating the FFR may occur in the LAD.

[0114] In Fig. 10, the FFR in a blood vessel, for example, the LCX (or RCA), in which the pressure sensor is positioned lower than the blood vessel entrance is shown. 1010 of Fig. 10 represents the FFR using the pressure difference value of the blood vessel excluding the pressure difference value due to gravity according to the height difference of the blood vessel, and 1020 of Fig. 10 may represent the FFR using the pressure difference value of the blood vessel corrected based on the pressure difference value due to gravity according to the height difference of the blood vessel. In the LCX (or RCA), the pressure sensor is positioned lower than the blood vessel entrance, and thus, the opposite tendency may be observed from that in the LAD. For example, in the LCX (or RCA), the FFR may be measured to be larger than the actual value due to the hydrostatic pressure difference. Accordingly, the problem of underestimating the FFR may occur in the LCX (or RCA).

[0115] FIG. 11 is a diagram for explaining a method for correcting a pressure difference value of a blood vessel according to one embodiment of the present disclosure. Referring to FIG. 11, a processor (e.g., a processor (220) of FIGS. 2 and 3) of an electronic device (e.g., an electronic device (100) of FIGS. 1 and 2) for correcting a pressure difference value of a blood vessel may, in step S1110, obtain at least one image (e.g., a blood vessel image (110) of FIG. 1) and photographing information (e.g., photographing information (120) of FIG. 1) of a subject's blood vessel. For example, the processor may obtain an image of a subject's blood vessel obtained by using a photographing device (e.g., a photographing device (400) of FIG. 4) in a state where a contrast agent is injected into the blood vessel of the subject. In addition, the processor may obtain photographing information of the photographing device at the time of photographing the at least one image. Here, the shooting information may include, for example, at least one of distance information between an X-ray generating device included in the shooting device (e.g., an X-ray generating device (454) of FIGS. 4 to 6) and an image acquisition device included in the shooting device (e.g., an image acquisition device (452) of FIGS. 4 to 6), distance information between the X-ray generating device and the subject to be examined, position information of an examination table (e.g., an examination table (510) of FIGS. 5 and 6), pixel spacing information of the image acquisition device, or angle information of the image acquisition device with respect to the subject to be examined (e.g., a first rotation angle (522) and a second rotation angle (524)).

[0116] In step 1120 (S1120), the processor can obtain height information of the gravity direction of the blood vessel included in at least one image. For example, the processor can obtain shooting information

[0117] Based on this, height information of the gravity direction of a blood vessel included in at least one image can be obtained.

[0118] According to one embodiment, the processor may obtain calibration information and shooting direction information based on shooting information of the shooting device for at least one image. Then, the processor may detect a centerline of a blood vessel included in the at least one image. Then, the processor may convert the centerline into three-dimensional coordinates based on the calibration information. For example, the processor may convert image coordinates in which the centerline is expressed into camera coordinates using internal parameters included in the calibration information. At this time, the internal parameters may include a matrix generated based on distance information between an X-ray generator and an image acquisition device and pixel spacing information of the image acquisition device. In addition, the processor may convert camera coordinates into world coordinates using external parameters included in the calibration information. At this time, the external parameters may include a rotation matrix generated based on angle information of the image acquisition device with respect to the subject and a transition vector indicating a camera position determined based on distance information between the rotation matrix and the X-ray generator and the subject. Additionally, the processor can use distance information between the X-ray generator and the subject and position information of the X-ray generator to move the world coordinates to coordinates based on the rotation center of the photographing device. Then, the processor can obtain height information in the direction of gravity of the blood vessel based on the three-dimensional coordinates of the center line.

[0119] According to one embodiment, the processor may obtain calibration information and shooting direction information based on shooting information of an imaging device for each of a plurality of blood vessel images. Then, the processor may detect a centerline of a blood vessel included in each of the plurality of blood vessel images. Then, the processor may reconstruct the centerline of the blood vessel included in each of the plurality of blood vessel images into a three-dimensional centerline based on the calibration information and the shooting information. For example, the processor may identify an epipolar line in a second image captured from a second direction of the imaging device among the plurality of blood vessel images based on a first centerline of a blood vessel detected in a first image captured from a first direction of the imaging device among the plurality of blood vessel images. Furthermore, the processor may identify a common point of the first centerline and the second centerline based on the second centerline and the epipolar line of the blood vessel detected in the second image. Furthermore, the processor may generate a three-dimensional centerline through triangulation based on the common point. Then, the processor may obtain height information in the direction of gravity of the blood vessel based on the coordinates of the three-dimensional centerline.

[0120] At step 1130 (S1130), the processor may calculate a height difference value between a first point and a second point of the blood vessel. For example, the processor may calculate a height difference value between the first point and the second point of the blood vessel based on the acquisition of height information in the direction of gravity of the blood vessel.

[0121] At step 1140 (S1140), the processor may calculate a difference in pressure due to gravity between a first point and a second point of the blood vessel. For example, the processor may multiply a difference in height between the first point and the second point of the blood vessel by a blood density and gravitational acceleration of the blood vessel to calculate a difference in pressure due to gravity between the first point and the second point of the blood vessel.

[0122] At step 1150 (S1150), the processor may compensate for a pressure difference between a first point and a second point of the blood vessel. For example, the processor may calculate a pressure difference between the first point and the second point of the blood vessel by adding a pressure difference due to gravity to a pressure difference due to a narrowing of the lesion's inner diameter. Here, the pressure difference due to a narrowing of the lesion's inner diameter may be a value measured using an FFR device. For example, the processor may calculate an FFR based on the compensated pressure difference of the blood vessel.

[0123] FIG. 12 is a diagram illustrating an artificial neural network model according to one embodiment of the present disclosure. Referring to FIG. 12 , the artificial neural network model (1200) is an example of a machine learning model. In machine learning technology and cognitive science, it may represent a statistical learning algorithm implemented based on the structure of a biological neural network, or a structure that executes the algorithm.

[0124] According to one embodiment, the artificial neural network model (1200) may represent a machine learning model having problem-solving capabilities by learning that nodes, which are artificial neurons that form a network by combining synapses like a biological neural network, repeatedly adjust the weights of synapses so that the error between the correct output corresponding to a specific input and the inferred output is reduced. For example, the artificial neural network model (1200) may include any probability model used in artificial intelligence learning methods such as machine learning and deep learning, a neural network model, etc.

[0125] According to one embodiment, the above-described pressure difference value correction model of the blood vessel (or the pressure difference value calculation model due to gravity of the blood vessel) can be generated in the form of an artificial neural network model (1200). For example, the artificial neural network model (1200) receives a blood vessel image that has captured a blood vessel and photographing information of a photographing device for the blood vessel image, estimates a pressure difference value due to gravity between a first point and a second point of the blood vessel based thereon, and corrects the pressure difference value between the first point and the second point of the blood vessel based on the pressure difference value due to gravity.

[0126] The artificial neural network model (1200) can be implemented as a multi-layer perceptron (MLP) composed of nodes in multiple layers and connections therebetween. The artificial neural network model (1200) according to the present embodiment can be implemented using one of the artificial neural network model structures including a multi-layer perceptron. The artificial neural network model (1200) can be configured with an input layer (1220) that receives input data (1210) (or input signal) from the outside, an output layer (1240) that outputs output data (1250) (or output signal) corresponding to the input data (1210), and n hidden layers (1230_1 to 1230_n) located between the input layer (1220) and the output layer (1240) that receive signals from the input layer (1220), extract features, and transmit them to the output layer (1240) (where n is a positive integer). Here, the output layer (1240) can receive signals from the hidden layers (1230_1 to 1230_n) and output them to the outside.

[0127] The learning method of the artificial neural network model (1200) may include a supervised learning method that learns to optimize problem solving by inputting a correct teacher signal (or label), and an unsupervised learning method that does not require a teacher signal. According to one embodiment, an electronic device (e.g., the electronic device (100) of FIGS. 1 and 2) according to one embodiment of the present disclosure may train the artificial neural network model (1200) by using a blood vessel image and photographing information of a photographing device for the blood vessel image.

[0128] According to one embodiment, the electronic device may generate training data for training an artificial neural network model (1200). For example, the electronic device may generate a training data set including a blood vessel image and photographing information of a photographing device for the blood vessel image. Then, the electronic device may train an artificial neural network model (1200) for calculating a pressure difference value due to gravity between a first point and a second point of a blood vessel based on the generated training data set. In addition, the electronic device may train an artificial neural network model (1200) for correcting a pressure difference value between the first point and the second point of a blood vessel based on the pressure difference value due to gravity.

[0129] According to one embodiment, the input variables of the artificial neural network model (1200) may include a blood vessel image in which the blood vessel is captured and photographing information of a photographing device for the blood vessel image. When the above-described input variables are input through the input layer (1220), the output variables output from the output layer (1240) of the artificial neural network model (1200) may be a pressure difference value due to gravity between a first point and a second point of the blood vessel or a pressure difference value between a first point and a second point of the blood vessel corrected based on the pressure difference value due to gravity.

[0130] In this way, a plurality of input variables and a plurality of corresponding output variables are respectively matched in the input layer (1220) and the output layer (1240) of the artificial neural network model (1200), and the synapse values ​​between the nodes included in the input layer (1220), the hidden layers (1230_1 to 1230_n), and the output layer (1240) are adjusted, so that learning can be performed so that the correct output corresponding to a specific input can be extracted. Through this learning process, the characteristics hidden in the input variables of the artificial neural network model (1200) can be identified, and the synapse values ​​(or weights) between the nodes of the artificial neural network model (1200) can be adjusted so that the error between the output variables calculated based on the input variables and the target output is reduced. In addition, the electronic device learns an algorithm that receives as input a blood vessel image in which a blood vessel is photographed and photographing information of a photographing device for the blood vessel image, and can learn in a manner that minimizes the loss with respect to the difference value of the pressure due to gravity between the first and second points of the blood vessel or the difference value of the pressure due to gravity (i.e., annotation information) between the first and second points of the blood vessel that has been corrected based on the difference value of the pressure due to gravity between the first and second points of the blood vessel or the difference value of the pressure due to gravity. Using the artificial neural network model (1200) learned in this way, the difference value of the pressure between the first and second points of the blood vessel that has been corrected based on the difference value of the pressure due to gravity between the first and second points of the blood vessel can be estimated.

[0131] The above flowchart and description are merely examples, and some embodiments may implement the system differently. For example, in some embodiments, the order of each step may be changed, some steps may be repeated, some steps may be omitted, or some steps may be added.

[0132] The above-described method may be provided as a computer program stored on a computer-readable recording medium for execution on a computer. The medium may be one that continuously stores a computer-executable program or one that temporarily stores it for execution or download. In addition, the medium may be various recording means or storage means in the form of a single or multiple hardware combinations, and is not limited to a medium directly connected to a computer system, but may also be distributed over a network. Examples of the medium may include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical recording media such as CD-ROMs and DVDs, magneto-optical media such as floptical disks, and those configured to store program instructions, including ROM, RAM, and flash memory. In addition, examples of other media may include recording or storage media managed by app stores that distribute applications, sites that supply or distribute various software, servers, etc.

[0133] The methods, operations, or techniques of the present disclosure may be implemented by various means. For example, these techniques may be implemented in hardware, firmware, software, or a combination thereof. Those skilled in the art will appreciate that the various exemplary logical blocks, modules, circuits, and algorithm steps described in connection with the disclosure herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various exemplary components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software will depend on the particular application and the design requirements imposed on the overall system. Those skilled in the art may implement the described functionality in various ways for each particular application, but such implementations should not be construed as departing from the scope of the present disclosure.

[0134] In a hardware implementation, the processing units used to perform the techniques may be implemented within one or more ASICs, DSPs, digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, electronic devices, other electronic units designed to perform the functions described herein, a computer, or a combination thereof.

[0135] Accordingly, the various exemplary logical blocks, modules, and circuits described in connection with the present disclosure may be implemented or performed by any combination of a general-purpose processor, a DSP, an ASIC, an FPGA or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or those designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.

[0136] In a firmware and / or software implementation, the techniques may be implemented as instructions stored on a computer-readable medium, such as random access memory (RAM), read-only memory (ROM), non-volatile random access memory (NVRAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable PROM (EEPROM), flash memory, a compact disc (CD), a magnetic or optical data storage device, etc. The instructions may be executable by one or more processors and may cause the processor(s) to perform certain aspects of the functionality described herein.

[0137] When implemented in software, the techniques described above may be stored on or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media, including any medium that facilitates transfer of a computer program from one place to another. Storage media may be any available media that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Also, any connection is properly termed a computer-readable medium.

[0138] For example, if the software is transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, digital subscriber line, or wireless technologies such as infrared, radio, and microwave are included within the definition of media. Disk and disc, as used herein, includes compact discs, laser discs, optical discs, digital versatile discs (DVDs), floppy disks, and Blu-ray discs, where disks typically reproduce data magnetically, whereas discs reproduce data optically using lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0139] A software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium may be coupled to the processor such that the processor can read information from, and write information to, the storage medium. Alternatively, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. Alternatively, the processor and the storage medium may reside as discrete components in the user terminal.

[0140] While the embodiments described above have been described as utilizing aspects of the presently disclosed subject matter in one or more standalone computer systems, the present disclosure is not limited thereto and may be implemented in conjunction with any computing environment, such as a network or distributed computing environment. Furthermore, aspects of the present disclosure may be implemented in multiple processing chips or devices, and storage may be similarly affected across multiple devices. Such devices may include personal computers, network servers, and portable devices.

[0141] While the present disclosure has been described in connection with certain embodiments herein, various modifications and variations may be made without departing from the scope of the present disclosure, which would be apparent to those skilled in the art. Furthermore, such modifications and variations are intended to fall within the scope of the claims appended to this specification.

Claims

1. A method for correcting a pressure difference value of a blood vessel, performed by at least one processor, A step of obtaining at least one image of a blood vessel of a subject using a photographing device and photographing information of the photographing device for the at least one image; A step of obtaining height information of the gravity direction of the blood vessel included in the at least one image based on the above shooting information; A step of calculating a difference value in height between a first point and a second point of the blood vessel based on the above height information; A step of calculating a difference value of pressure due to gravity between the first point and the second point of the blood vessel based on the difference value of the height; and A step of correcting the pressure difference value between the first point and the second point of the blood vessel based on the pressure difference value due to the gravity. A method for correcting the pressure difference value of a blood vessel, including:

2. In paragraph 1, The above shooting information is, A method for correcting a pressure difference value of a blood vessel, comprising at least one of first distance information between an X-ray generating device included in the photographing device and an image acquisition device included in the photographing device, second distance information between the X-ray generating device and the subject, position information of an examination table, pixel spacing information of the image acquisition device, or angle information of the image acquisition device with respect to the subject.

3. In paragraph 2, The step of obtaining the above height information is: A step of obtaining calibration information and shooting direction information based on the above shooting information; A step of detecting a centerline of the blood vessel included in at least one image; A step of converting the center line into three-dimensional coordinates based on the calibration information; and A step of obtaining height information in the direction of gravity of the blood vessel based on the three-dimensional coordinates of the center line. A method for correcting the pressure difference value of a blood vessel, including:

4. In paragraph 3, The step of converting the above center line into 3D coordinates is: A step of converting the image coordinates in which the center line is expressed into camera coordinates using internal parameters included in the calibration information, wherein the internal parameters include a matrix generated based on the first distance information and the pixel spacing information; A step of converting the camera coordinates into world coordinates using external parameters included in the calibration information, wherein the external parameters include a rotation matrix generated based on the angle information and a transition vector indicating a camera position determined based on the rotation matrix and the second distance information; and A step of moving the world coordinates to coordinates based on the rotation center of the photographing device using the second distance information and the position information of the X-ray generating device. A method for correcting the pressure difference value of a blood vessel, including:

5. In paragraph 1, The at least one image includes a plurality of images of the blood vessels of the subject taken from different directions using the photographing device, The step of obtaining the above height information is: A step of obtaining calibration information and shooting direction information based on the shooting information of the shooting device for each of the plurality of images; A step of detecting the center line of the blood vessel included in each of the plurality of images; A step of reconstructing the centerline of the blood vessel included in each of the plurality of images into a three-dimensional centerline based on the calibration information and the shooting information; and A step of obtaining height information in the direction of gravity of the blood vessel based on the coordinates of the three-dimensional center line. A method for correcting the pressure difference value of a blood vessel, including:

6. In paragraph 5, The step of reconstructing the centerline of the blood vessel included in each of the plurality of images into a three-dimensional centerline is as follows: A step of identifying an epipolar line in a second image captured in a second direction of the photographing device among the plurality of images based on a first center line of the blood vessel detected in a first image captured in a first direction of the photographing device among the plurality of images; A step of identifying a common point of the first center line and the second center line based on the second center line and the epipolar line of the blood vessel detected in the second image; and A step of creating the three-dimensional center line through triangulation based on the above common point. A method for correcting the pressure difference value of a blood vessel, including:

7. In paragraph 1, The step of calculating the difference value of the above pressure is: A step of calculating a difference in pressure due to gravity between the first point and the second point of the blood vessel by multiplying the difference in height by the blood density and gravitational acceleration of the blood vessel. A method for correcting the pressure difference value of a blood vessel, including:

8. In paragraph 1, A step of calculating information related to blood flow characteristics based on the difference value of the above-mentioned corrected pressure. A method for correcting the pressure difference value of a blood vessel, further comprising:

9. A computer program stored in a computer-readable recording medium for executing the method according to any one of paragraphs 1 to 8 on a computer.

10. In electronic devices, memory; and At least one processor connected to said memory and configured to execute at least one computer-readable program contained in said memory, At least one program above, Obtaining at least one image of a blood vessel of a subject using a photographing device and photographing information of the photographing device for the at least one image, Based on the above shooting information, height information of the gravity direction of the blood vessel included in the at least one image is obtained, Based on the above height information, the difference value of the height between the first point and the second point of the blood vessel is calculated, Based on the difference value of the height, the difference value of the pressure due to gravity between the first point and the second point of the blood vessel is calculated, An electronic device comprising commands for correcting a pressure difference value between the first point and the second point of the blood vessel based on a pressure difference value due to gravity.

Images