417 results about "Blood velocity" patented technology

A method comprises receiving a user input to select a first point and a second point from a medical image, extracting a plurality of blood vessel regions from a plurality of frame images of the medical image, determining a plurality of first regions associated with the first point and a plurality of second regions associated with the second point, determining a first frame image and a second frame image with the contrast agent arriving at the first point and the second point, based on a change in pixel intensity for each of the plurality of first regions and the plurality of second regions, and computing the blood flow velocity from the first point to the second point based on a time interval between the first frame image and the second frame image and on a distance between the first point and the second point.

The present disclosure provides a method for correcting a resting blood flow velocity on the basis of an interval time between angiogram images, comprising: acquiring, in an angiography state, an average blood flow velocity Vh from a coronary artery inlet to a distal end of a coronary artery stenosis (S100); acquiring a time difference Δt between start times of two adjacent bolus injections of contrast agent (S200); obtaining a correction coefficient K according to the time difference Δt (S300); obtaining a resting blood flow velocity Vj according to the correction coefficient K and the average blood flow velocity Vh (S400), as well as an apparatus configured for implementing the above method. The disclosure obtains the resting blood flow velocity Vj according to the correction coefficient K and the average blood flow velocity Vh.

The invention relates to the field of physiological status real-time monitoring, provides a virtual patient physiological status real-time monitoring method and system based on digital twinning, and is used for solving the problems of non-linear combination deviation and multi-source data synchronization lag of virtual patient physiological status monitoring caused by dependence on a static model and one-way feedback. The method comprises the steps that a valve three-dimensional model is built based on aorta CT data, and a simulation model containing motion conditions is built in combination with a fluid mechanics equation; the blood flow pressure difference and vortex parameters of valve opening and closing are calculated in real time, an optical fiber virtual sensor is embedded in the topological surface of the valve to simulate blood flow deformation, and a valve state mechanical signal is output; parameters and signals are input into a digital twin engine, particle trajectories and refractive indexes are adjusted to generate a visual interface, blood flow velocity-pressure gradient spatio-temporal data are extracted, model boundary conditions are reversely corrected, and valve movement is synchronized with the physiological state of a patient. According to the technical scheme, heart valve movement is simulated in real time, and the real heartbeat rhythm of the patient is automatically matched.

A method and system for determining a regional weakening (RW) value in a blood vessel using ultrasonic imaging. A set of images of a portion of a given patient's body collected over time is received. A set of measurements representing the movement of the tissue of the blood vessel is received, and the set of measurements is determined based on the set of images. The movement of the wall and lumen at least partially indicates strain. A blood flow velocity value in the blood vessel is determined based on a Doppler image, and an RW parameter indicating the state of weakening in a region of the blood vessel is determined based on at least the set of measurements, thrombus burden, and blood flow velocity value. A map showing the circumference of the blood vessel including the regional weakening value and the strain value may be displayed.

A blood vessel pressure difference calculation method and apparatus based on angiographic data at a single body position, and an electronic device and a storage medium. The method comprises: acquiring angiographic data at a single body position (S1); determining an actual lumen model of a target blood vessel and an actual lumen geometry parameter of the actual lumen model (S2); determining a blood flow velocity V in the target blood vessel (S3); determining a proximal end point and a distal end point of a blood vessel segment of interest (S4); determining a reference lumen model of the target blood vessel and a reference lumen geometry parameter of the reference lumen model (S5); determining a difference change function D(xp) on the basis of the difference between a reference lumen geometry parameter and an actual lumen geometry parameter at any position p between the proximal end point and the distal end point (S6); and calculating a pressure difference ΔP between the position p and the proximal end point on the basis of the difference change function D(xp) and the blood flow velocity V (S7).

The invention provides a cervical vertebra segmentation and key point detection method based on a diffusion model, and relates to the technical field of medical image processing, and the method carries out the denoising processing of a cervical vertebra image through the diffusion model, improves the image quality, and lays a foundation for the subsequent segmentation and key point detection. A cervical vertebra region and key point positions can be accurately extracted by combining a model of a deep learning technology, and reliable data support is provided for bone age staging; the bone age staging based on the results can objectively and quantitatively evaluate the growth and development degree of a patient and assist a doctor in making a personalized orthodontic treatment scheme, and in addition, in combination with a stress distribution diagram generated by a biomechanical model and a self-adaptive segmentation model of a preprocessed image, a segmentation strategy can be adjusted according to individual differences, so that the accuracy of bone age staging is improved. The precision and the robustness are improved; meanwhile, parameters such as blood flow velocity and temperature distribution are incorporated into a machine learning model, new indexes are provided for cervical vertebra bone age staging, and the individuation and accuracy of evaluation are enhanced.

The invention discloses an ultrasonic positioning microscopic imaging method and system based on joint resolution perception and vision Mangbar, and the method specifically comprises the steps: obtaining and preprocessing a plurality of modal angiography data, generating a microbubble motion sequence in combination with blood flow velocity field simulation data, and constructing a data set; inputting the data set into a mixed hierarchical feature pyramid fusion network, carrying out probability density estimation on a microbubble position based on a real-time multi-scale density field estimation algorithm, and introducing a resolution perception algorithm to enhance microbubble features to obtain a plurality of short-track images; performing dynamic feature decoupling and time-frequency analysis on the short-track image, extracting and encoding velocity component features and spatial-temporal context information of a vascular structure, and constructing a double-branch processing network based on visual Mangbar to obtain images respectively reflecting forward motion contribution and backward motion contribution, and finally generating a high-resolution blood vessel image through image fusion. The method has an important value for improving the efficiency and precision in microvascular imaging.

A method comprises receiving a user input to select a first point and a second point from a medical image, extracting a plurality of blood vessel regions from a plurality of frame images of the medical image, determining a plurality of first regions associated with the first point and a plurality of second regions associated with the second point, determining a first frame image and a second frame image with the contrast agent arriving at the first point and the second point, based on a change in pixel intensity for each of the plurality of first regions and the plurality of second regions, and computing the blood flow velocity from the first point to the second point based on a time interval between the first frame image and the second frame image and on a distance between the first point and the second point.

The invention discloses an AI-based auxiliary system for clinical teaching of cerebrovascular diseases, particularly relates to the field of disease management, and comprises a multi-modal information summarization module, a feature extraction module, a cross-modal deduction module, a dynamic incremental learning module, a virtual case generation module and a teaching evaluation feedback generation module. According to the AI-based auxiliary system for clinical teaching of cerebrovascular diseases, millisecond-level time domain alignment is carried out through a multi-modal information gathering module, a mapping relation table of image space coordinates and physiological signal timestamps is established, the problem of time sequence deviation caused by asynchronous processing of sub-channels is solved, and time-space alignment of multi-source data is achieved; feature decoupling of images and physiological signals is achieved through a feature extraction module, and relevance between cross-modal features is enhanced; dynamic information of blood flow velocity and blood pressure fluctuation of blood vessels is fused into attention scores through a cross-modal deduction module, and a causal relationship between variables is established, so that time-space consistency of clinical logic during deduction of complex cases is improved.

Disclosed are approaches to non-invasively characterize a tumor or other lesion in a region of interest (ROI) based on various analyses of magnetic resonance imaging (MRI) data. The MRI data may correspond to ultrafast dynamic contrast enhanced MRI (DCE-MRI) and high spatial resolution DCE-MRI scans, and diffusion-weighted MRI (DW-MRI) scans of the ROI. Vasculature metrics may be determined, and tumor-associated blood flow velocity and / or tumor interstitial pressure may be obtained using the vasculature metrics as inputs to a computational fluid dynamics model. A combination of morphological vascular metrics and functional vascular metrics may be used to characterize the tumor. Malignancy, aggressiveness, treatment response, and other features of tumors or other lesions, in the breast or other regions of a patient, may be characterized through disclosed analyses of MRI data.

The invention discloses a femoral artery paracentesis post-operation pressure-controlled hemostasis device and a monitoring intelligent control system thereof, and relates to the technical field of medical apparatuses and instruments, and the femoral artery paracentesis post-operation pressure-controlled hemostasis device comprises an assembly panel; the air bags are arranged at the bottom of the assembly panel; the air pump is arranged at the top of the assembly panel and used for controlling the air bags to contract; the control piece is arranged at the top of the assembly panel and used for controlling the air pump; the Doppler probe is arranged at the bottom of the assembly panel and used for detecting the blood flow speed of the far end of a puncture point, the hemostasis safety and efficiency are remarkably improved through multi-mode intelligent control and a real-time feedback mechanism, the vein area is accurately recognized and avoided in combination with ultrasonic and infrared spectrum analysis of the artery positioning module, the thrombus forming probability is effectively reduced, and the blood flow speed of the far end of the puncture point is detected. The pressure-time optimization model dynamically shortens the compression time (target 3 hours) based on the real-time hemostatic effect, and improves the comfort of the patient while ensuring the hemostatic effect.

The invention provides a real-time processing method for endoscopic image blood vessel enhancement and microcirculation evaluation, which comprises the following steps of: processing an original endoscopic image, and locally enhancing a brightness channel through a contrast-limited adaptive histogram equalization technology; self-adaptive frequency domain-space domain decomposition is realized based on local texture complexity analysis; performing multi-scale Hessian matrix blood vessel detection on the low-frequency component; applying a directional Gabor filter bank to the high-frequency component; spatial-temporal feature fusion is realized through multi-resolution pyramid optical flow calculation; synchronously completing blood vessel probability prediction, blood vessel diameter estimation and blood flow direction prediction by using a lightweight multi-task deep learning network; the blood flow velocity is analyzed and calculated based on a speckle mode, the perfusion density is subjected to accelerated statistics through an integrogram, and vascular morphological parameters are extracted by adopting an improved skeleton algorithm. According to the invention, an enhanced blood vessel visualization effect and a real-time microcirculation quantitative evaluation function can be provided, and the overall improvement of the endoscope image processing quality and efficiency is realized.

The present invention belongs to the field of flexible electronics, and specifically is a flexible polymer ultrasonic probe. The flexible polymer ultrasonic probe of the present invention is a multi-layer structure, which includes a shielding layer, a backing layer, an upper electrode, a piezoelectric layer, a lower electrode, a matching layer, and a coupling layer from top to bottom; all functional layers are made of polymers and their composite materials, have very good flexibility, and can withstand complex deformations such as bending and twisting. The flexible polymer ultrasonic probe can emit ultrasonic waves under the excitation of electrical signals as an ultrasonic transmitting unit, and can also collect ultrasonic signals as an ultrasonic receiving unit. The flexible polymer ultrasonic probe can be made into a patch for industrial flaw detection of irregular surface objects and long-term health monitoring of the human body. For example, based on the ultrasonic Doppler principle, long-term continuous monitoring of blood flow velocity in human blood vessels can be achieved.

The invention discloses a bedside skin flap blood flow monitoring and early warning device and computing equipment, and the device comprises a skin flap tissue perfusion monitoring module which comprises a probe housing, a microcirculation blood flow velocity sensor, a tissue oxygenation degree sensor and a flexible connecting arm; the data acquisition and transmission module is used for receiving the blood flow velocity data and the oxygenation degree data through a data line and carrying out analog-to-digital conversion and data packaging; the central processing unit comprises a data storage module, a data analysis module and an early warning module; the data analysis module comprises a baseline establishment sub-module, an anomaly detection sub-module and a trend prediction sub-module; and the early warning module is used for displaying a red alarm through a bedside display screen and sending a short message alarm containing the patient name, the bed number, the early warning type and the severity information to a medical staff mobile terminal through the wireless notification module. According to the invention, the abnormal condition of skin flap blood perfusion can be found and predicted in time, and the workload of medical staff is reduced.

The invention discloses a thyroid ultrasound image diagnosis method based on deep learning, and the method comprises the following steps: collecting a thyroid ultrasound original image set, and carrying out the preprocessing; performing focus segmentation on the standardized thyroid ultrasound image set; performing morphological constraint and boundary refinement; calculating the blood flow direction, blood flow velocity and blood flow power of each thyroid focus area and neighborhood; generating a preliminary fusion feature map based on a feature adaptive deep learning network, and fusing the preliminary fusion feature map with the thyroid focus blood flow feature vector set; obtaining a thyroid focus detection list through thyroid focus benign and malignant discrimination branches; and generating thyroid focus structured diagnosis data records based on the thyroid focus detection list, and writing the thyroid focus structured diagnosis data records into a computer-aided diagnosis system. According to the method, deep learning and multi-modal blood flow features are fused, intelligent diagnosis of the thyroid focus is achieved, and the method has the advantages of being high in precision, high in interference resistance and structured in result.

An embodiment of the present application provides a method for determining blood flow velocity and a Doppler blood flow detection device, wherein the method comprises: obtaining an emission angle, which is the angle between the direction in which a signal is emitted by a transmitting element in the Doppler blood flow detection device and the direction in which blood flow moves in a blood vessel to be detected; obtaining the distance between a transmitting element and a receiving element in the Doppler blood flow detection device and the distance between the transmitting element and the blood vessel to be detected; determining a receiving angle according to the emission angle, the distance between the transmitting element and the receiving element, and the distance between the transmitting element and the blood vessel to be detected, wherein the receiving angle is the angle between the direction in which a signal is received by a receiving element in the Doppler blood flow detection device and the direction in which blood flow moves; determining a blood flow velocity measurement value according to the emission angle and the receiving angle; in this way, a more accurate blood flow velocity measurement value can be obtained.

The invention provides an intelligent diagnosis and treatment method, system and equipment based on individualized blood pressure management, a computer readable storage medium and application thereof, and relates to the field of intelligent medical treatment. The method comprises the following steps: acquiring blood pressure, electroencephalogram signals, cerebral blood flow velocity and arterial blood pressure data of a subject; analyzing based on the electroencephalogram signal and cerebral blood flow velocity data of the subject to obtain a neurovascular coupling index; obtaining an individualized blood pressure range based on the nerve and blood vessel coupling index and the arterial blood pressure data of the subject; whether the blood pressure of the subject is within the individualized blood pressure range or not is judged, and when the blood pressure of the subject is not within the individualized blood pressure range, information prompt for blood pressure control is output. According to the method disclosed by the invention, the blood pressure management is guided by determining the individualized blood pressure range of the cardiovascular and cerebrovascular disease patient, valuable resources are provided for researchers and clinicians in the field of cardiovascular and cerebrovascular disease diagnosis and treatment, and the method has important scientific research significance and clinical value.

The invention discloses a three-dimensional blood flow imaging method based on blood flow velocity, a medium, equipment and a system, and belongs to the technical field of imaging. The method comprises the following steps: acquiring an OCT original spectral signal of a measured object; the OCT original spectral signals are converted into OCT intensity signals, time integral speckle intensity is obtained through grouping integration, and pixels of the same space area are obtained to form a pixel set; calculating a time integral speckle contrast of each spatial position in the pixel set, and obtaining statistics of all pixels in the pixel area; calculating the blood flow velocity according to the statistical magnitude; the blood flow velocity of each spatial position is obtained, and a three-dimensional blood flow image is generated. According to the method, the time integral speckle contrast of each spatial position in the pixel set is calculated, and the blood flow velocity of the pixel area is calculated according to the time integral speckle contrast, so that the fluid velocity detection upper limit is greatly expanded, and the problem of low blood flow velocity measurement accuracy in the three-dimensional blood flow imaging graph is solved.

The invention relates to the technical field of medical instruments, in particular to an internal fistula blood vessel detection system for hemodialysis, which comprises a data acquisition module for acquiring ultrasonic data, an impedance value, tremor intensity and a pressure spectrum; the mode determining module is used for determining a detection mode of the internal fistula blood vessel based on the tortuosity index and determining massage frequency and air bag pressure according to the blood vessel compliance index; the stenosis analysis module is used for determining whether the internal fistula blood vessel is stenosis or not based on the stenosis risk characterization parameter and determining whether the stenosis degree of the internal fistula blood vessel is in a reasonable range or not according to the blood flow velocity characterization value; the frequency adjusting module determines and adjusts the massage frequency based on the ratio; the injury analysis module is used for determining whether the internal fistula blood vessel is injured or not in the dialysis process on the basis of the bioelectrical impedance change rate and determining whether the internal fistula blood vessel injury is in a reasonable range or not after dialysis according to the tremor intensity change value; the pressure adjusting module determines and adjusts the pressure of the air bag based on the difference value. The accuracy of internal fistula blood vessel detection is improved.

The invention discloses a brain arteriovenous malformation vascular structure lumped model simulation method and system, and the method comprises the steps: obtaining the three-dimensional image data of a preset region of the head of a human body, and recognizing a brain arteriovenous malformation vascular mass region in the three-dimensional image data; constructing a blood vessel three-dimensional structure model, and acquiring three-dimensional space coordinate data of each voxel in the cerebral arteriovenous malformation vascular cluster region in the model; calibrating an inlet and an outlet of the blood vessel three-dimensional structure model and corresponding pressure set values and / or flow velocity set values; extracting a plurality of skeleton points of the blood vessel based on the blood vessel three-dimensional structure model to obtain a microscopic blood vessel network; based on the three-dimensional space coordinate data, the length and the average diameter of each blood vessel in the microscopic blood vessel network are obtained, and the flow resistance of the blood vessels is calculated; based on the pressure set value and the flow velocity set value of the blood vessel three-dimensional structure model and the flow resistance of each blood vessel, the blood flow velocity and pressure distribution data of each blood vessel are calculated through a lumped parameter model, and the hemodynamic characteristics of the cerebral arteriovenous malformation blood vessel are obtained.

A wearable device with a light source and an optical sensor. In some embodiments, a system includes a wearable device for being worn by a subject and for measuring a first biomarker of a blood vessel of the subject. The wearable device may include a first light source, and a plurality of optical detectors. The system may be configured: to perform a photoplethysmography measurement with each of the plurality of optical detectors, the first biomarker being a blood volume; or to perform a speckleplethysmography measurement with each of the plurality of optical detectors, the first biomarker being a blood flow velocity.

Planning cardiac surgery is a complex task. Current heart models are mostly static and provide no functional information or personalization apart from structural information from imaging modalities like MRI, CT etc. The embodiments of present disclosure addresses unresolved problem of generating a personalized four dimensional cardiac model that integrates blood flow velocity, pressure profile and volume on three-dimensional cardiac structure, providing a comprehensive tool for pre or post-surgical planning and analysis. Unlike existing techniques, which often rely on separate assessments of cardiac anatomy and hemodynamics, using invasive methods, the present disclosure provides a 4D cardiac model that captures the person specific dynamic interaction between cardiac structures and blood flow throughout the cardiac cycle. Further, the 4D cardiac model enables clinicians to visualize and quantify complex flow patterns and pressure distributions within the region of interest in the heart, facilitating precise surgical planning and outcome prediction especially in pediatric heart surgery.

System and method for measuring hypertension conditions of a subject is disclosed. The disclosed system and method includes thermal sensors for capturing thermal images and / or videos of a body part; and a processing engine to detect a predefined region of the body part in each frame of the captured images and / or videos. The processing engine segments one or more portions from the detected predefined region in each frame of the captured images and / or videos to identify a region of interest comprising arteries in the one or more segmented portions. Based on the identified region of interest, the engine extracts pixel values from each frame of the captured images and / or videos to determine parameters associated with a blood flow velocity and a blood pressure of the subject. Further a type of hypertension and a risk score for the hypertension condition based on the determined parameters using computational models are measured.

A non-invasive, passive, fully automated heart sound-based system and method is provided that provides estimation of blood velocity, tissue movement, and lumen size parameters for heart assessment. The system uses a computer processor and software to receive PCG acoustic signals from one or more sensors and simultaneously receive electrocardiogram (ECG) signals from one or more sensors attached to the patient. A phonocardiogram (PCG) processing system and method computes metrics of indices of echocardiogram parameters of heart tissue movement and valve blood flow for evaluation.

The invention relates to a fractional flow reserve calculation method and device, electronic equipment and a readable medium. The method comprises the following steps: constructing a three-dimensional geometric model of a target blood vessel; performing dimension reduction simulation on the three-dimensional geometric model to obtain first blood flow velocity distribution and first pressure distribution of the target blood vessel; the first blood flow velocity distribution and the first pressure distribution serve as initial conditions of three-dimensional simulation, iterative calculation is conducted on the three-dimensional geometric model, and target blood flow velocity distribution and target pressure distribution of the target blood vessel are obtained; and calculating the fractional flow reserve of the target blood vessel according to the target blood flow velocity distribution and the target pressure distribution. According to the scheme provided by the invention, the calculation efficiency can be greatly improved under the condition that the calculation precision is not influenced.

The invention relates to the technical field of medical image analysis methods, in particular to a lung drainage basin analysis method based on hemodynamics, which comprises the following steps: acquiring lung CT image data; acquiring lung anatomy data and clinical medical knowledge; generating a pulmonary artery blood vessel tree model based on the lung CT image data; establishing a hemodynamic model according to the pulmonary artery blood vessel tree model; calculating a blood flow velocity field and a pressure gradient field based on the hemodynamic model; according to the pressure gradient field, executing a watershed watershed segmentation algorithm to obtain a lung watershed division result; according to the method, an analysis report containing a lung drainage basin division result is generated, the segmentation precision of a lung blood vessel network is greatly improved by adopting an advanced image processing technology and a blood vessel tracking algorithm, and the method can more accurately reflect individual differences and blood flow characteristics in a pathological state by dynamically adjusting boundary conditions and blood parameters. And meanwhile, an efficient numerical solution algorithm is adopted, so that the calculation complexity is remarkably reduced.

An ultrasound diagnostic apparatus (1) includes a first vascular wall detection unit (10) that detects a vascular wall in a minor axis direction by analyzing a B-mode image including a minor axis image of a blood vessel, a first blood vessel diameter calculation unit (11) that calculates a first blood vessel diameter from the vascular wall in the minor axis direction, a second vascular wall detection unit (12) that detects a vascular wall in a major axis direction by analyzing the B-mode image including a major axis image of the blood vessel, a second blood vessel diameter calculation unit (13) that calculates a second blood vessel diameter from the vascular wall in the major axis direction, a blood flow velocity calculation unit (15) that calculates a blood flow velocity based on Doppler data in a Doppler gate set on the B-mode image, and a blood flow rate measurement unit (16) that measures a blood flow rate based on the vascular wall in the major axis direction or the minor axis direction and the blood flow velocity, in which in a case where the second blood vessel diameter is within a determined range with respect to the first blood vessel diameter, the blood flow rate is automatically measured.

The invention provides a patch type thrombus monitoring and NO release closed-loop system for treating venous thrombosis, which comprises a flexible patch substrate on which a sensor module is integrated, and the sensor module comprises a blood flow velocity sensor, a biological impedance sensor, an acceleration sensor and a temperature sensor, the acquisition units are respectively used for acquiring blood flow velocity v at a target vein, related parameters of vascular resistance R, limb movement states and skin temperature of a patch area; the NO release module is used for releasing NO to act on the venous thrombosis part; the control module comprises a signal processing unit and a control unit and is used for receiving the signal output by the sensor module and operating a closed-loop control algorithm to generate an NO release control instruction; and the power supply module provides electric energy for the sensor module, the control module and the NO release module. The invention provides a patch type closed-loop system which integrates thrombus multi-mode monitoring, decision making, NO release assisting and treatment mode self-adaptive switching.

To provide an estimation method of a recirculation rate enabling estimation of a recirculation rate without being limited by a preparation location of a blood marker or an arrangement location of detection means of the blood marker.SOLUTION: An estimation method of a recirculation rate includes the steps of: acquiring data representing an amount of change in blood concentration after recirculation when a blood marker is added to blood to be extracorporeally circulated, data representing a relation between an amount of change in blood concentration after recirculation and blood concentration, and data representing a relation between the amount of change in blood concentration after recirculation and a blood flow rate; creating a model by multivariate analysis or machine learning to obtain a regression equation or a conversion model, with the amount of change in blood concentration after recirculation, blood concentration and a blood flow rate used as an explanatory variables and the recirculation rate as an objective variable; acquiring data representing the amount of change in blood concentration, blood concentration and a blood flow rate of blood flowing through an arterial line or a venous line; and inputting treatment data to the regression equation or the conversion model to estimate the recirculation rate.SELECTED DRAWING: Figure 3A

The invention relates to the technical field of blood vessel stenosis grading, in particular to a blood vessel stenosis degree grading system based on coronary angiography images. The method comprises the following steps: dividing a vascular skeleton line of an angiography image into vascular segments based on a bifurcation point, and determining a stenosis point on the vascular segment according to the blood flow velocity difference of the vascular segment at the front edge position of a contrast agent in each frame of angiography image and a neighborhood angiography image; according to the blood vessel diameter difference between each bifurcation point and the other bifurcation points and the distance between the other bifurcation points and the main blood vessel section, a reference adaptation degree is obtained, a reference point of each bifurcation point is selected, and according to the blood flow speed difference between each bifurcation point and the branch blood vessel section of the reference point and the reference adaptation degree, narrow points in the bifurcation points are screened; and grading the blood vessel stenosis degree based on the blood vessel diameter of the stenosis point. The blood vessel skeleton line is divided into two conditions of the blood vessel segment and the bifurcation point to analyze the blood vessel physiological stenosis position, and the accuracy of positioning the pathological stenosis position in the coronary artery is improved.