49 results about "Stenosis degree" patented technology

The invention discloses a coronary artery virtual stent implantation method and system based on haemodynamics analysis. The coronary artery virtual stent implantation method comprises the steps that CTA image data of a patient are read, plaque is identified, a vascular three-dimensional image model is constructed, the plaque is removed, and the position of the plaque is recorded; the physiological parameters of the patient is received, a CFD boundary condition is set, and CFD calculating is conducted; according to a three-dimensional vascular form, a plaque characteristic and FFR values throughout blood vessels, a lesion is identified; according to the identified lesion, a stent specification database and a virtual stent implantation strategy, an implantation scheme is generated, and a new vascular three-dimensional geometric model is generated; under the new three-dimensional geometric model, fluid calculation is conducted again, according to a preset selecting standard, an optimal stent implantation scheme is output. According to the coronary artery virtual stent implantation method and system, blood vessel stenosis degree calculating, stent implantation strategy generating and quantitative evaluating of the virtual stent implantation effect are completed automatically, the operation scheme is planned accurately, the doctor decision efficiency is improved effectively, and the risk of dependence on the artificial judgment is reduced.

A system analyzes angiogram image data, including video data, in order to extract vasculature information. Advanced image processing and machine learning techniques are used in pre-processing, frame selection, and vasculature segmentation to remove classes of artifacts from angiogram videos, and specifically from frames selected as having a sufficient amount of image data. From segmentation, accurate vasculature diameters are calculated, and, in some examples, stenoses and / or the extent of stenosis is automatically determined and displayed.

The invention discloses a method for establishing an intracranial vessel simulation three-dimensional stenosis model based on transfer learning. The method comprises the following steps: acquiring a bright blood image group and an enhanced black blood image group of an intracranial vessel; preprocessing each bright blood image and the corresponding enhanced black blood image to obtain a first bright blood image and a first black blood image; performing image registration by using mutual information based on Gaussian distribution sampling and a registration method of an image pyramid; groupingthe registered bright blood images to obtain MIP images in all directions; obtaining a two-dimensional blood vessel segmentation image based on the MIP image and the fundus blood vessel image; performing back projection synthesis on the two-dimensional blood vessel segmentation image to obtain first three-dimensional blood vessel body data, and obtaining an intracranial blood vessel simulation three-dimensional model by utilizing the second three-dimensional blood vessel body data; and for each section of blood vessel in the model, obtaining a numerical value of a target parameter representingthe stenosis degree of the section of blood vessel, and marking the intracranial blood vessel simulation three-dimensional model by utilizing the numerical value of the target parameter to obtain a simulated three-dimensional intracranial blood vessel stenosis analysis model.

The invention discloses a carotid artery stenosis degree calculation method and device and a storage medium, and the method comprises the steps: S1, receiving a neck MRA image, and carrying out the interlayer registration of a first sequence and a second sequence in the neck MRA image, so as to form an interlayer corresponding relation; S2, transverse blood vessels are extracted from all layers ofimages of the registered first sequence, and the blood vessel area of each transverse blood vessel is calculated; S3, extracting a transverse blood target from each layer of image of the registered second sequence, and calculating the blood area of each transverse blood target; S4, according to the interlayer corresponding relation, the blood vessel area of each transverse position blood vessel and the blood area of each corresponding transverse position blood target are substituted into a calculation formula, and a plurality of carotid artery stenosis degrees are obtained through calculation; and S5, outputting the maximum value in the plurality of carotid artery stenosis degrees as the carotid artery stenosis degree of the neck MRA image. According to the embodiment of the invention, the carotid artery stenosis degree can be automatically calculated, so that the diagnosis efficiency and accuracy of doctors are improved.

A system analyzes angiogram image data, including video data, in order to extract vasculature information. Advanced image processing and machine learning techniques are used in pre-processing, frame selection, and vasculature segmentation to remove classes of artifacts from angiogram videos, and specifically from frames selected as having a sufficient amount of image data. From segmentation, accurate vasculature diameters are calculated, and, in some examples, stenoses and / or the extent of stenosis is automatically determined and displayed.

The present invention discloses the correlation between circular endothelial progenitor cell (EPC) and coronary artery pathological change. It is test proved that the number and migration and adhesion power of circular EPC is high correlated with the stenosis degree of coronary artery, so that circular EPC may be used as the reference index for diagnosing the stenosis degree of coronary artery. The present invention also provides method and kit for detecting the stenosis degree of coronary artery based on the said correlation.

The present disclosure provides a method for predicting a healthy radius of a blood vessel path, a method for predicting a candidate stenosis of a blood vessel path, and a device for predicting a degree of vascular stenosis. The method for predicting the healthy radius includes: obtaining the vascular radius of the vascular path; using a processor, detecting the peak value of the vascular radius of the vascular path; and using the processor, predicting the healthy radius by performing regression on the radius peak. The device for predicting the degree of vascular stenosis includes a processor, which is configured to realize by executing executable instructions: acquiring image units along the centerline within the candidate stenosis range of each vascular path; and based on the acquired image units, using a learning network to determine The stenosis of each vascular path, wherein the learning network is based on a convolutional neural network and a recurrent neural network. The device can automatically determine the candidate stenosis and detect the stenosis according to the candidate stenosis range, which can significantly reduce the calculation load, improve the detection efficiency and effectively avoid missed detection.

The present invention proposes an arteriovenous fistula external hemodynamics physical simulation model device, the simulated blood circuit includes a simulated heart container, a radial artery blood pressure simulation container, a cephalic vein blood pressure simulation container and a fistula simulator equipped with a measuring device; The installation height of the arterial blood pressure simulation container and the cephalic vein blood pressure simulation container is higher than that of the simulated heart container; the fistula simulator is equipped with a fistula simulation cavity surrounded by elastic simulated skin; the input end of the fistula simulation cavity is respectively connected to the radial artery blood pressure simulation container , the cephalic vein blood pressure simulation container, and the output port is connected to the simulated heart container; when the simulation is performed, the fistula simulation cavity reaches the required deformation, and the simulated blood in the radial artery blood pressure simulation container and the cephalic vein blood pressure simulation container flows back through the fistula simulation cavity To simulate the heart container, the measuring device of the fistula simulator measures the pressure and flow velocity of the blood flowing through the input end and the output end; the invention can establish a set of stable blood vessel models with controllable stenosis.

The invention discloses a method for establishing a simulated three-dimensional blood vessel stenosis analysis model. The method comprises the following steps: acquiring a bright blood image group and an enhanced black blood image group of a blood vessel part; performing image registration on each bright blood image by using a registration method based on mutual information and an image pyramid by taking the corresponding enhanced black blood image as a reference to obtain a registered bright blood image group; establishing a blood vessel simulation three-dimensional model by using the registered bright blood image group; aiming at each section of blood vessel in the blood vessel simulation three-dimensional model, segmenting from three preset orientations to obtain a two-dimensional section diagram of each orientation; performing corrosion operation on the blood vessel in the two-dimensional section diagram of each orientation, and recording target corrosion times when the blood vessel is corroded to a single pixel; according to the target corrosion times corresponding to the section of blood vessel in the three directions, obtaining a numerical value of a target parameter representing the stenosis degree of the section of blood vessel; and marking the blood vessel simulation three-dimensional model by using the numerical value of the target parameter of each section of blood vessel to obtain a simulated three-dimensional blood vessel stenosis analysis model.

The invention discloses a coronary artery virtual stent implantation method and system based on haemodynamics analysis. The coronary artery virtual stent implantation method comprises the steps that CTA image data of a patient are read, plaque is identified, a vascular three-dimensional image model is constructed, the plaque is removed, and the position of the plaque is recorded; the physiological parameters of the patient is received, a CFD boundary condition is set, and CFD calculating is conducted; according to a three-dimensional vascular form, a plaque characteristic and FFR values throughout blood vessels, a lesion is identified; according to the identified lesion, a stent specification database and a virtual stent implantation strategy, an implantation scheme is generated, and a new vascular three-dimensional geometric model is generated; under the new three-dimensional geometric model, fluid calculation is conducted again, according to a preset selecting standard, an optimal stent implantation scheme is output. According to the coronary artery virtual stent implantation method and system, blood vessel stenosis degree calculating, stent implantation strategy generating and quantitative evaluating of the virtual stent implantation effect are completed automatically, the operation scheme is planned accurately, the doctor decision efficiency is improved effectively, and the risk of dependence on the artificial judgment is reduced.