31 results about "Coronary vessel" patented technology

A method of performing 3D vessel tree reconstruction includes providing segmented binary angiography images, applying a distance transform to the images, and generating distance transformed binary angiography images. The set of distance transformed binary angiography images are provided to a trained 3D vessel reconstruction machine learning model capable of reconstructing 3D vessels. The 3D vessel tree reconstruction machine learning model includes a multi-stage convolutional neural network comprising a multi-stage architecture with (i) a vessel centerline stage, and (ii) a radius reconstruction stage. Resultant 3D reconstructed vessel trees may be used in performing clinical assessment of coronary vessel health, and occlusion.

A method of performing 3D vessel tree reconstruction includes providing segmented binary angiography images, applying a distance transform to the images, and generating distance transformed binary angiography images. The set of distance transformed binary angiography images are provided to a trained 3D vessel reconstruction machine learning model capable of reconstructing 3D vessels. The 3D vessel tree reconstruction machine learning model includes a multi-stage convolutional neural network comprising a multi-stage architecture with (i) a vessel centerline stage, and (ii) a radius reconstruction stage. Resultant 3D reconstructed vessel trees may be used in performing clinical assessment of coronary vessel health, and occlusion.

The present application relates to a kind of DSA coronary vessel segmentation deep learning method of edge and topological feature, comprising the following steps: obtaining DSA coronary angiography image dataset and corresponding coronary vessel label dataset;Data is input into deep learning network, the deep learning network is end-to-end U type deep learning network, include improved bidirectional Transformer module and multi-scale semantic fusion module, and encoder and decoder are connected by jump connection and multi-scale semantic fusion module;Coronary vessel segmentation model is trained in three stages using the composite loss function comprising Dice loss, Focal loss, edge loss and topological loss, the segmentation model of the training completion can be carried out complete segmentation to the coronary vessel in DSA coronary angiography picture;Using composite evaluation index, the overall segmentation accuracy of segmentation model, edge segmentation accuracy and the ability of keeping topological consistency are comprehensively evaluated.

The application discloses a blood vessel image segmentation method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring an initial blood vessel image, determining a coronary skeleton image of the initial blood vessel image; determining each skeleton point on the skeleton line in the coronary skeleton image, and determining a skeleton branch point in each skeleton point based on the degree of each skeleton point; acquiring a skeleton connected path between any adjacent skeleton branch points, and determining a venous branch line segment in the coronary skeleton image based on the skeleton connected path; and determining a coronary segmentation image of the initial blood vessel image based on the initial blood vessel image and the venous branch line segment. The technical scheme disclosed by the application removes the venous branch in the initial blood vessel image to obtain a coronary vessel image of the initial blood vessel image, solves the problem of low coronary segmentation accuracy of blood vessels in the prior art, and achieves the technical effect of improving the coronary segmentation accuracy.

The invention provides a comprehensive assessment method for coronary artery function, which comprises the following steps of: based on boundary conditions, performing hemodynamic numerical simulation calculation on each finite element model by adopting a traditional computational fluid mechanics solution mode or a reduced order solution mode to obtain simulated hemodynamic parameters; based on a comparison result between the simulated hemodynamic parameters and the reference hemodynamic parameters corresponding to each finite element model, performing iterative optimization on the outlet resistance of each blood vessel branch and the simulated hemodynamic parameters in the boundary conditions to obtain optimized outlet resistance of each target blood vessel branch and target simulated hemodynamic parameters; and determining the fractional flow reserve and the microcirculation resistance index by using the outlet resistance of each target blood vessel branch and the target simulated hemodynamic parameters. According to the method, coupling iterative calculation is carried out on the microcirculation resistance by establishing the coronary vessel tree, the microcirculation resistance index and the fractional flow reserve are determined at the same time based on the calculation result, and the reliability of overall coronary function calculation is improved.

This invention discloses a 3D-printed helical biodegradable anti-inflammatory vascular stent and its preparation method, belonging to the field of vascular stents. The invention uses multiple helical support wires arranged into a tubular shape, with the ends connected in a serpentine transitional manner. The helical support wires are connected by connecting ribs, and the surface is coated. This invention is biodegradable after use, avoiding the harm caused by permanent retention in the body, and has a lower restenosis rate compared to metal stents. The surface of the vascular stent is coated with a spermidine-containing coating to prevent immune rejection of the implanted vascular stent, thereby addressing the problems of inflammation and intimal hyperplasia. The helical structure facilitates contraction and expansion, has good bending flexibility, and the added connecting ribs increase the radial support performance of the vascular stent, better achieving the effect of vascular remodeling. This invention has significant implications in terms of biodegradability, anti-immune rejection, and mechanical properties, and can be used for treatment in different locations such as peripheral and coronary vessels.

The application relates to a coronary microcirculation vascular resistance acquisition method and system based on a layered myocardial model, which comprises the following steps: establishing a coronary vessel model from medical images; generating a side vessel for the coronary artery; regarding the coronary artery and the side vessel as main vessels, fitting and constructing an outer surface of a myocardial model according to the outlet position of the main vessels, establishing an inner surface of the myocardial model based on a similar principle to the outer surface, and ensuring that the volume of the model is the myocardial volume value; using an ellipsoid surface for layered interpolation; selecting a point P in the outermost layer and connecting the main vessel outlet to generate a microcirculation vessel; selecting a point T outside the current layer and cooperating with the nearest microcirculation vessel to generate a bifurcated microcirculation vessel; gradually advancing to the inner layer to form bifurcation and ensure the bifurcation number of each layer; and calculating the resistance value of the main vessel outlet. Compared with the prior art, the application considers the distribution of the coronary artery at various levels of the myocardium under real conditions, so that the calculated resistance value is more accurate and has the specificity of a patient.

The invention provides a coronary blood vessel segmentation system and method fusing high and low frequency features. The method comprises the steps that a cascade multi-scale stripe convolution module is cascaded with stripe convolution operations of different scales, and features are extracted in a multi-level mode from the global mode to the local mode; the high and low frequency feature separation adaptive module separates an input feature map into high-frequency and low-frequency components, adaptive enhancement is carried out on the high-frequency and low-frequency components respectively, and finally the enhanced high-frequency and low-frequency components are fused; the multi-scale stripe high and low frequency enhancement module firstly inputs the input feature map into the cascade multi-scale stripe convolution module to extract features, then inputs the output feature map into the high and low frequency feature separation adaptive module to carry out high and low frequency separation and adaptive enhancement, and finally outputs the obtained feature map. Based on the technical scheme of the invention, the segmentation precision and the detail capture capability can be improved; local details and a global structure can be clearly distinguished, and the problem of excessive segmentation or insufficient segmentation is effectively avoided; the robustness of the model is enhanced, and the blood vessel can be stably and accurately segmented.

The application belongs to the technical field of medicine, and particularly relates to application of acacetin or 6-hydroxyflavone in preparation of anti-angina pectoris drugs, and aims to solve the problems of adverse reactions such as blood pressure drop, reflex tachycardia and the like caused by non-selective vasodilation of existing anti-angina pectoris drugs, wherein the drug improves myocardial blood supply by selectively dilating coronary vessels of the heart, wherein acacetin dilates coronary vessels of the heart by inhibiting cardiac coronary vessel myosin light chain kinase and activating myosin light chain phosphatase, and 6-hydroxyflavone dilates coronary vessels of the heart by inhibiting protein kinase C and enhancing myosin light chain phosphatase activity; and the acacetin or 6-hydroxyflavone significantly reduces the symptoms of myocardial ischemia of rats caused by isopropyl adrenaline, improves characteristic ECG abnormal changes of angina pectoris, does not affect heart rate and systemic blood pressure, and is safer, thereby providing a potential drug selection for anti-angina pectoris treatment.

The application provides a non-invasive coronary blood flow evaluation method based on multi-phase CTA and Bayesian inference, comprising the following steps: acquiring multi-phase coronary CTA images of a target to be evaluated, and extracting coronary vessel deformation waveform data from the multi-phase coronary CTA images; generating posterior probability distribution estimation results of coronary blood flow rate through a pre-established Bayesian inference framework and the coronary vessel deformation waveform data; and generating coronary blood flow rate evaluation results corresponding to the target to be evaluated according to the posterior probability distribution estimation results. The application uses a Bayesian framework to simultaneously estimate multiple physiological parameters, and identifies parameter interactions through posterior correlation analysis, thereby improving inversion accuracy.

The application belongs to the technical field of medical images, and discloses a coronary vessel center line extraction method, device, equipment and storage medium. The method comprises the following steps: acquiring a coronary segmentation image and an aorta segmentation image, and detecting the coronary segmentation image to obtain a first left coronary starting point and a first right coronary starting point; performing inflation processing on the aorta segmentation image to obtain a target aorta segmentation image; performing intersection segmentation on the coronary segmentation image based on the target aorta segmentation image to obtain a final coronary segmentation image; detecting the final coronary segmentation image, and determining a left coronary end point and a right coronary end point after detecting a second left coronary starting point and a second right coronary starting point; and determining a left coronary vessel center line and a right coronary vessel center line based on the first left coronary starting point, the first right coronary starting point, the left coronary end point and the right coronary end point. In this way, the coronary vessel center line can be accurately extracted when the coronary vessel origin is abnormal.

This application provides a method, apparatus, and storage medium for calculating coronary artery calcium scores, comprising: segmenting an initial three-dimensional medical image of the cardiac region from a plain coronary CT image using an image segmentation model; identifying calcified plaque regions in the initial three-dimensional medical image to determine at least one target region image and the location information of each image; identifying the coronary vessel category in each image by recognizing the input consisting of the target region image and the image location information; performing overall recognition of the initial three-dimensional medical image using a second coronary classification model to determine the calcified plaque regions included in the initial three-dimensional medical image, the location information of each region, and the category of coronary vessels; and calculating the calcium score for the calcified regions identified by both models to obtain the total coronary artery calcium score. Thus, the method provided in this application can quickly and accurately calculate the coronary artery calcium score based on plain CT scans.

The application relates to a method and system for obtaining coronary end microcirculation vascular resistance based on vascular growth, and the method comprises the following steps: acquiring medical images, and extracting a myocardial model and a coronary vascular model respectively; generating collateral vessels in the coronary vascular model; regarding all coronary vessels and collateral vessels as main vessels, and obtaining the position coordinates and the vascular radius; randomly selecting a point P in the myocardial model, connecting the point P with the outlet of the main vessel, and generating microcirculation vessels for each outlet of the main vessel; randomly selecting a point T in the point cloud file of the myocardial model, connecting the point T with the nearby microcirculation vessels, and generating multiple bifurcated microcirculation vessels, until the radius of all vessel outlets in the generated vascular tree is smaller than a preset vascular threshold; and calculating the resistance value of each outlet of the main vessel. Compared with the prior art, the coronary end microcirculation vascular resistance value calculated based on the reestablished microcirculation vascular model is more accurate and has the specificity of patients.

The application relates to a coronary vessel segmentation method and device and a storage medium. The segmentation method comprises the following steps: acquiring a three-dimensional CTA image containing a coronary vessel; inputting the three-dimensional CTA image into a trained bifurcation point detection network to obtain bifurcation point information of the coronary vessel, wherein the bifurcation point detection network is constructed based on a first deep full convolution network; and inputting the three-dimensional CTA image and the bifurcation point information into a trained blood vessel segmentation network to determine a segmentation result of the coronary vessel, wherein the blood vessel segmentation network is constructed based on a second deep full convolution network. The coronary vessel segmentation method can quickly and accurately segment the coronary vessel from the three-dimensional CTA image in an end-to-end manner, and the reliability and accuracy of the blood vessel segmentation are further improved due to the bifurcation points in the coronary vessel as auxiliary information.

Embodiments of the present application provide an image processing method and device and a storage medium. In the embodiments of the present application, a coronary vessel region and a lesion sub-region containing a plaque in the coronary vessel region in a medical image can be automatically identified, feature extraction and quantification are respectively performed on the coronary vessel region and the lesion sub-region, first medical features and second medical features are obtained, and the first medical features and the second medical features are sent into a pre-trained image classification model to obtain a classification result of the medical image. In the whole process, potential information in the medical image can be deeply mined, the accuracy of identifying the classification result of the medical image is improved, and the demand of actual application is met.

1. Name of the product in this design: A three-dimensional imaging window for a graphical user interface for registering and fusing coronary CTA and coronary angiography image information in electronic devices. 2. Intended use of this design: for use in an electronic device. 3. The key design features of this product are the content displayed on the user interface. 4. The image or photograph that best illustrates the design's key features: the front view. 5. Purpose of the graphical user interface: The graphical user interface is used to display the image information fusion after the registration of coronary CTA and coronary angiography images, which facilitates the simultaneous observation of information on coronary vessels and plaque components in different modalities and dimensions, thereby providing guidance for clinical analysis or surgery. In the main view, click the "Volume Render View" button at the top of the "CT 3DView" area to enter the interface change state shown in Figure 1. In the interface change state diagram 1, click the "MIP Mode" selection box at the bottom of the "CT 3DView" area to enter the interface change state diagram 2. 6. Other situations requiring explanation: This design is a partial protection design, wherein the part outside the red semi-transparent covered area is the part for which the design patent is sought.

The invention relates to the technical field of computer vision, in particular to a four-stage progressive vascular plaque medical image segmentation and STL three-dimensional reconstruction method, which comprises the following steps of: firstly, carrying out initial segmentation on an input medical image, and positioning a heart ROI (Region of Interest); then, performing blood vessel coarse segmentation in the heart ROI to obtain a coarse segmentation result; based on the coarse segmentation result, performing fine segmentation on the blood vessel to restore the fine structure of the blood vessel and obtain a fine blood vessel contour result; then, based on the fine blood vessel contour result, plaques on the blood vessel wall are segmented, the positions, boundaries, forms and attached blood vessel segment information of the plaques are determined, and a final segmentation result is obtained; and finally, converting the final segmentation result to generate a three-dimensional model for clinical analysis. According to the reconstruction method provided by the invention, the problems of dependence on manual intervention, low efficiency, poor result consistency, weak modal adaptability, non-universal output format and the like in the existing cardiac coronary vessel and plaque reconstruction method are solved.

Disclosed in the present invention are an automatic detection method and system for coronary artery dissections. The method comprises: first, collecting clinical coronary artery angiography images, and processing the images to form a data set, so as to train and verify a YOLOv8 model; processing a coronary artery angiography image needing to be tested, and then inputting same into the YOLOv8 model for the identification and localization of an FL in the image; using a constructed SO(2)-UNet model to perform feature extraction and semantic segmentation on coronary arteries in a located region of the image after identification and localization, and accurately segmenting coronary vessels; and further identifying a dissection region in the segmented coronary vessels, and visually presenting same. In the present invention, YOLOv8 is used to perform object detection, a large number of images are quickly and accurately tested in a short time, and coronary artery dissections in the images are automatically identified to realize an automatic detection process, thereby significantly improving the efficiency and accuracy of diagnosis.

1. Name of the product in this design: Graphical User Interface for Controlling Coronary CTA and Coronary Angiography Image Information for Electronic Devices. 2. Intended use of this design: for use in an electronic device. 3. The key design features of this product are the content displayed on the user interface. 4. The image or photograph that best illustrates the design's key features: the front view. 5. Purpose of the graphical user interface: The graphical user interface is used to control the image information after the registration of coronary CTA and coronary angiography images, which facilitates the simultaneous observation of information on coronary vessels and plaque components in different modalities and dimensions, thereby providing guidance for clinical analysis or surgery. In the main view, double-click the blood vessel in the middle "CT 3DView" area image to enter the interface change state diagram 1. The selected blood vessel is highlighted in the "CT 3DView" and "XA View" areas. In the interface change state diagram 1, double-click another blood vessel in the middle "CT 3DView" area graphic to enter the interface change state diagram 2. In the interface change state diagram 2, after moving the three blue, green and red sliders in the "LumenView" area in the lower left corner, you will enter the interface change state diagram 3, which will change the selected blood vessel segment and blood vessel position and update the quantitative information. The blue, green and red indicator lines in each area image will also move accordingly.

The application relates to a coronary vessel segmentation method, device, equipment, storage medium and program product. The method comprises the following steps: inputting an acquired to-be-segmented image into a segmentation network for initial segmentation, obtaining an initial vessel segmentation image of a coronary vessel in the to-be-segmented image; determining an initial tube lumen density attenuation gradient (TAG) image corresponding to the coronary vessel according to the initial vessel segmentation image of the coronary vessel; inputting the to-be-segmented image and the initial TAG image into the segmentation network for target segmentation, and determining a target vessel segmentation image of the coronary vessel; wherein the image value of the coronary vessel from the first end to the end in the initial TAG image changes linearly. The method can improve the accuracy of the obtained coronary segmentation result.

An example medical system includes a memory configured to store angiography data of a patient, the angiography data including pre-stimulation angiography data and post-stimulation angiography data. The pre-stimulation angiography data includes at least one angiography image of a blood vessel including a patient captured prior to delivery of stimulation to the blood vessel. The post-stimulation angiography data includes at least one angiography image including the blood vessel captured after initiation of delivery of stimulation to the blood vessel. The medical system includes processing circuitry communicatively coupled to the memory. The processing circuit is configured to obtain pre-stimulation angiography data and to obtain post-stimulation angiography data. The processing circuit is configured to determine a dimensional difference of the blood vessel between the pre-stimulation angiography data and the post-stimulation angiography data and output an indication of the dimensional difference.

The application relates to a method and device for automatically reconstructing a coronary three-dimensional model, the method comprising the following steps: obtaining a first angle image, a second angle image, a first angle key frame and a second angle key frame based on a DSA image sequence, performing key point pair detection on the first angle key frame and the second angle key frame to obtain a matching point pair, obtaining a two-angle projection relationship before correction according to the first angle image and the second angle image information, and obtaining a projection relationship after correction in combination with the matching point pair; performing semantic segmentation on the first angle key frame and the second angle key frame to obtain a first angiography angle graph and a second angiography angle graph of a target blood vessel; obtaining a first center line, a first contour line, a second center line and a second contour line according to the first angiography angle graph and the second angiography angle graph; and combining the projection relationship after correction to obtain a three-dimensional center line and a three-dimensional contour of the target blood vessel, so that an accurate three-dimensional center line and three-dimensional contour of the target blood vessel are obtained.

An interventional ostium occlusion catheter includes a catheter tube with at least one port at a first end, a tip at a second end, and a central lumen, with a positioning component and an occlusion component on the surface of the catheter tube close to the tip. A method of coronary intervention using the catheter includes maneuvering the catheter to an ostium; inserting the catheter into a coronary vessel; activating the positioning component and the occlusion component; and delivering an infusion via the lumen. An interventional system for improving management of ischemic cardiac tissue during acute coronary syndromes includes the catheter; a blood infusion device that delivers controlled reperfusate; and a ventricular unloading device that manipulates myocardial oxygen demand in a coronary chamber. The operator can mitigate reperfusion-related and oxygen-related tissue injury by precisely modulating oxygen re-exposure when re-establishing flow and when using a ventricular unloading device.

This invention presents a cross-modal distillation-coupled coronary plaque classification method, aiming to address the limitations of CTA (Coronary Artery Therapy) due to its low spatial resolution and susceptibility to artifacts, while high-precision IVUS (Intravascular Ultrasound) requires inserting the probe into the vessel, potentially causing discomfort and complications for patients. To combine the advantages of both CTA and IVUS, this invention utilizes artificial intelligence to model the mapping relationship between CTA and IVUS. Through automatic delineation and identification of coronary vessels and plaques, the high-resolution characteristics of IVUS overcome the limitations of CTA, endowing CTA images with the discriminative capabilities of IVUS.

The invention relates to a rapid marking method for a coronary CTA blood vessel, computer equipment and a computer program product. The rapid marking method comprises the steps that a coronary three-dimensional model is constructed based on a coronary CTA sequence image, a coronary center line is obtained through extraction based on the coronary three-dimensional model, and a single coronary center line is obtained through extraction according to the coronary center line; straightening and reconstructing a corresponding single blood vessel in the coronary artery three-dimensional model along the central line of the single coronary artery to obtain a straightened single blood vessel model; performing section sampling on the single blood vessel model according to an interception plane passing through the central line of the single coronary artery to obtain a section image; and performing image segmentation on the cross-section image to obtain a coronary vessel edge line, mapping the coronary vessel edge line to the single vessel model, and obtaining the single vessel model marked with coronary vessel boundary information. Compared with a scheme of directly carrying out coronary vessel boundary segmentation on the three-dimensional single vessel model, the method has the advantages that the operation difficulty is reduced, and the computing power cost is saved.

The invention discloses a traditional Chinese medicine prescription for treating gout and promoting uric acid metabolism and a preparation method thereof, and belongs to the technical field of traditional Chinese medicine prescriptions for gout, the traditional Chinese medicine prescription is prepared from the following raw materials in parts by weight: 1 part of chicory root (extract), 1 part of semen plantaginis, 1 part of dandelion, 1 part of sargentgloryvine stem, 1 part of sunflower disc alkaloid, 1 part of parasitic loranthus and 1 part of rhizoma smilacis glabrae. The preparation method comprises the step of grinding the chicory root (extract), the semen plantaginis, the dandelion, the sargentgloryvine stem, the sunflower disc alkaloid, the loranthus parasiticus and the dry leaves and branches of the rhizoma smilacis glabrae into powder to obtain the product. Before taking, the medicinal material powder is brewed with water at 70-80 DEG C. The formula can treat gout and promote uric acid metabolism in the body. As an orally taken prescription for soaking in water, the traditional Chinese medicine composition has the effects of (1) reducing swelling and removing stasis, inducing diuresis, promoting diuresis, treating stranguria, dispelling wind and relieving pain, ventilating, dredging collaterals and activating blood, clearing liver and benefiting gallbladder, tonifying liver and kidney, strengthening muscles and bones, protecting cardiovascular system, invigorating stomach and promoting digestion, expelling toxin, reducing blood pressure, blood fat, blood sugar and cholesterol, expanding coronary vessels, resisting inflammation and enhancing immunity; (2) gouty stones can be dissolved, and uric acid metabolism in the body can be accelerated; and (3) relieving mild acute gouty arthritis, namely reducing uric acid, dissolving calculus and regulating the acid-base balance degree of the body by the sunflower alkali to improve the symptoms such as uric acid level increase and gouty arthritis caused by purine metabolism disorder, neutralizing the uric acid, maintaining the acid-base balance in the body, reducing the attack frequency of gout and the like.

The application belongs to the technical field of medical image processing, and discloses a coronary vessel center line extraction method, device, equipment and storage medium. The method comprises the following steps: determining a first center line of a first coronary vessel according to a coronary vessel starting point, a coronary vessel terminal end point and a center distance intensity graph of the first coronary vessel; dividing the first center line into multiple sub-center lines, and then sampling each sub-center line to obtain N sampling points, and determining a corresponding direction vector of each sampling point on a sub-center line tangent; determining an image cutting graph of the N sampling points based on the N sampling points and the corresponding direction vectors; inputting the image cutting graph of the N sampling points into a target CNN convolutional neural network to obtain high-dimensional feature data; inputting the high-dimensional feature data into a target Transformer network to obtain a corresponding offset of each sampling point; and obtaining a second center line based on the first center line and the offset. The first center line can be optimized to obtain the second center line.

The application relates to a myocardial bridge detection device in a coronary angiography sequence, comprising: a coronary vessel segmentation module for segmenting a coronary vessel through a neural network model, the model being composed of a CNN and a transformer structure, and being capable of effectively extracting local information and global information of the vessel; a coronary vessel information calculation module for calculating information including the diameter, length and start-stop coordinates of the vessel according to a vessel segmentation map, establishing a coronary vessel tree containing all the vessels, and calculating matching vessels between the angiography sequences; and a coronary myocardial bridge detection module for realizing the detection of the coronary myocardial bridge by calculating the stenosis degree of the same vessel in the angiography sequence.