505 results about "Mr angiography" patented technology

Systems and methods for four-dimensional analysis of a patient's coronary arteries and myocardial wall. An example method includes accessing angiographic x-ray images of one or more arteries, with the x-ray images depicting the arteries from respective angles, with each x-ray image being associated with a cardiac phase of cardiac phases, and with the cardiac phases being included in a cardiac cycle. A three-dimensional model of the arteries is generated for each cardiac phase based on a subset of the x-ray images which are associated with the cardiac phase. A four-dimensional representation of the arteries is generated throughout the cardiac cycle based on the three-dimensional models for the cardiac phase. Information associated with the four-dimensional presentation is presented.

The invention provides an acute cerebral apoplexy early-stage intelligent screening and early warning method and system based on deep learning, and relates to the technical field of medical imaging and artificial intelligence, and the method comprises the steps: obtaining a multi-temporal angiography image of the brain of a patient through a pulse-type dynamic imaging scheme, extracting hemodynamic features through a double-flow feature extraction network, and obtaining a multi-temporal angiography image of the brain of the patient; and constructing a vasculopathy risk distribution diagram by combining a vascular structure analysis model, and marking a potential embolism risk area. Furthermore, in combination with tissue perfusion parameters obtained by multispectral imaging and brain tissue function parameters obtained by electroencephalogram signals, an ischemic penumbra region is identified by using a self-adaptive threshold segmentation model. And finally, based on the ischemic penumbra area, the tissue perfusion parameters and the brain tissue function parameters, calculating a risk level by using a hierarchical decision model with a space-time attention mechanism, and generating a corresponding clinical intervention scheme. According to the invention, the early accurate screening and risk early warning of acute cerebral apoplexy can be realized, and the clinical intervention efficiency is improved.

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.

An apparatus for performing a vascular assessment is disclosed. The apparatus creates a three-dimensional model that is representative of a coronary vessel tree of a patient based on at least two angiographic images. The apparatus estimates first blood flow resistance values for points along at least some vascular segments of the coronary vessel tree using vascular geometrical dimensions of the three-dimensional model. The apparatus also estimates second blood flow resistance values for the points along the at least some vascular segments of the coronary vessel tree using a volume of a crown of the vascular segment downstream from the respective point. The apparatus determines fractional flow reserve (“FFR”) by calculating a ratio of the first blood flow resistance values and the second blood flow resistance values at each of the points along the at least some vascular segments of the coronary vessel tree.

Methods, apparatuses, and systems for digital image analysis for device navigation in tissue are disclosed. The disclosed system uses real-time angiography and artificial intelligence to navigate an end effector of a surgical robot through a patient's vasculature to provide a surgical intervention. Digital imaging is performed that enables three-dimensional mapping of the patient's vasculature. Locations and movement of the end effector of the surgical robot are determined. The end effector is used to perform an intervention such as the removal of a blood clot or delivery of a drug for dissolving a blood clot.

Systems and methods for post-PCI coronary analysis. An example method includes accessing a plurality of angiographic images depicting at least one vessel of a patient's heart, the angiographic images including two or more post-percutaneous coronary intervention (post-PCI) images and one or more diagnostic images, wherein the post-PCI images depict a PCI location in which a PCI is included to revascularize a lesion, and wherein the diagnostic images depict the lesion; receiving, via a user interface presenting the post-PCI images, user input specifying positions of the PCI location in the post-PCI images; determining an index indicative of vascular function based on the angiographic images, wherein the index is derived based on a three-dimensional model of the portion of the patient's heart, and wherein individual portions of the diagnostic images depicting the lesion are masked during generation of three-dimensional model; and presenting, via the user interface, summary information associated with PCI, the summary information including at least the determined index.

The invention relates to an ischemic cerebrovascular disease angiography image segmentation analysis method, which comprises the following steps: detecting gray transition abnormity, structural fracture and artifact delay signals in an angiography image, extracting negative segmentation priori points indicating a suspected ischemic area, aggregating to form a priori abnormal area, introducing a symmetric disturbance test mechanism, and analyzing the angiography image according to the priori abnormal area. Judging a potential blocked or abnormal blood vessel segment, and dynamically adjusting the segmentation threshold of the region; establishing a local interference window in the judgment region, extracting frequency and rhythm features of density stripes, and performing compensation segmentation on interrupted blood vessel segments caused by unsteady pulse change through a convolution kernel scaling strategy; calculating a texture difference value and a frequency domain response offset, if the offset is within a preset physiological tolerance range, triggering an interpolation completion mechanism, and generating a credible completion layer for subsequent calibration reference; and performing dynamic feedback adjustment and continuous calibration on the previously segmented path by analyzing the multi-path divergence degree of the vascular branch end point and the path offset change in the image sequence.

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 system (100) for reconstructing digital subtraction angiography, DSA, images (110) representing a region of interest (120) in an object (130), is provided. The system includes one or more processors (140) configured to: receive (S110) cone beam projection data (150) acquired during a portion of a revolution of a source-detector arrangement (160s, 160d) of a cone beam X-ray imaging system (170) around the object (130); reconstruct (S120) the cone beam projection data (150) acquired from one or more orientations within a first angular range (Dq1), into a 3D mask image (170) representing the region of interest (120); and reconstruct (S130) the cone beam projection data (150) acquired from one or more orientations within a second angular range (Dq2), into a temporal sequence of 3D DSA images (110) representing the region of interest (120), based on the reconstructed 3D mask image (170).

The present disclosure provides to generate a 3D visualization of a vessel from intravascular ultrasound (IVUS) images. In particular, the present disclosure provides to reduce jitter between frames of an IVUS recording to provide a smoother appearance of a longitudinal view of the vessel from the IVUS image frames and to construct a 3D visualization of the vessel from the jitter compensated IVUS image frames.

Systems and methods for post-PCI coronary analysis. An example method includes accessing a plurality of angiographic images depicting at least one vessel of a patient's heart, the angiographic images including two or more post-percutaneous coronary intervention (post-PCI) images and one or more diagnostic images, wherein the post-PCI images depict a PCI location in which a PCI is included to revascularize a lesion, and wherein the diagnostic images depict the lesion; receiving, via a user interface presenting the post-PCI images, user input specifying positions of the PCI location in the post-PCI images; determining an index indicative of vascular function based on the angiographic images, wherein the index is derived based on a three-dimensional model of the portion of the patient's heart, and wherein individual portions of the diagnostic images depicting the lesion are masked during generation of three-dimensional model; and presenting, via the user interface, summary information associated with PCI, the summary information including at least the determined index.

The invention discloses a vascular intervention operation robot control method and system. The method comprises the following steps: processing an angiography image; comprising the steps of image enhancement, image segmentation and image correction after segmentation, carrying out feature extraction on a processed image, obtaining a blood vessel state index value by combining blood vessel image features and other information of a patient, obtaining a guide wire control parameter according to the blood vessel state index value, and correcting the control parameter. And controlling the vascular interventional operation robot based on the corrected PID control parameter value. The control parameters of the guide wire are adjusted according to different blood vessel states, so that the advancing control of the guide wire is matched with the blood vessel states, and the entering safety and the advancing efficiency of the guide wire are ensured.

The present disclosure provides to generate a side branch mask from an extravascular image of a vessel using an ensemble of machine learning (ML) models. The side branch mask can be generated by inferring, using several initial ML models, indications of side branches from an image frame and inferring, using a post-processing ML model, the side branch mask from the indication of side branches.

The invention discloses a binocular X-ray guide wire three-dimensional positioning method, a binocular X-ray guide wire three-dimensional positioning device and binocular X-ray guide wire three-dimensional positioning equipment based on epipolar geometry and a storage medium. The method comprises the steps that two to-be-processed images collected by two X-ray scanning devices in the biplane digital subtraction angiography system for a target object in a guide wire intervention state are acquired, and the to-be-processed images comprise intervention guide wires; conducting guide wire positioning on the two to-be-processed images based on projection matrixes which are obtained through pre-calibration and respectively correspond to the two X-ray scanning devices, and determining path information of the interventional guide wire, the path information comprising first position information of the interventional guide wire; obtaining an expected path of the interventional guide wire, and determining an offset error of the interventional guide wire based on expected position information of the interventional guide wire in the expected path and the first position information; the expected path of the intervention guide wire is updated based on the offset error, accurate positioning of the intervention guide wire and updating of the expected path are achieved, and accurate data support is provided for subsequent treatment.

Example systems and techniques are disclosed that may determine at least one treatment strategy for a lesion. An example system may include memory configured to store clinical guidance and / or informatics for a PCI procedure and processing circuitry communicatively coupled to the memory. The processing circuitry may be configured to determine the plurality of treatment pathways. The processing circuitry may be configured to obtain angiogram imaging data of a coronary vasculature of a patient. The 2024 / 058837 processing circuitry may be configured to determine the clinical guidance and / or informatics based at least in part on the angiogram imaging data. The processing circuitry may be configured to output for display the angiogram imaging data and at least a portion of the clinical guidance and / or informatics, wherein the at least a portion of the clinical guidance and / or informatics is overlaid onto the angiogram imaging data.

The present invention provides an early intelligent screening and warning method and system for acute stroke based on deep learning, which relates to the field of medical imaging and artificial intelligence technology, including obtaining multi-phase angiography images of the patient's brain through a pulsed dynamic imaging scheme, extracting hemodynamic characteristics using a dual-stream feature extraction network, and constructing a vascular lesion risk distribution map in combination with a vascular structure analysis model to mark potential embolism risk areas. Further, combining tissue perfusion parameters obtained by multispectral imaging and brain tissue function parameters obtained by electroencephalogram signals, an adaptive threshold segmentation model is used to identify the ischemic penumbra area. Finally, based on the ischemic penumbra area, tissue perfusion parameters, and brain tissue function parameters, a hierarchical decision model with a spatiotemporal attention mechanism is used to calculate the risk level and generate a corresponding clinical intervention plan. The present invention can achieve early and accurate screening and risk warning of acute stroke, and improve the efficiency of clinical intervention.

A method for generating a subtraction image for digital subtraction angiography to reduce noise and movement artifacts. Obtaining a plurality of mask images of an object takes place before administering a contrast agent into the object and obtaining a map of the object after administering a contrast agent into the object. A first sum image is obtained from the plurality of mask images in that the plurality of mask images is summed in each case multiplied by an individual weighting. The individual weightings for each of the plurality of mask images are automatically determined by an optimization method, and the subtraction image is ascertained by subtraction of the sum image from the map.

The invention relates to the technical field of medical imaging engineering, in particular to an angiography and tissue elastography device and method.The device comprises a reference layer arranged on the surface of biological tissue, and the elasticity modulus of the reference layer is known; the excitation unit is used for applying compression excitation to the surface of the reference layer and inducing the reference layer and the biological tissue to deform through excitation; the imaging unit is used for performing frequency domain optical coherence tomography on the reference layer and the biological tissue and collecting interference intensity signal sequences of the reference layer and the biological tissue along with wavelength change; and the upper computer is used for controlling the excitation unit and the imaging unit to act synchronously, and performing angiography, structural imaging and elastic imaging of the biological tissue according to the Young modulus of the reference layer and the interference signal sequence. Therefore, the problem that in the prior art, angiography and tissue elasticity are carried out separately, and only blood vessel network information or tissue elasticity characteristics can be provided is solved.

The invention relates to the technical field of model reconstruction, in particular to a method for reconstructing a coronary artery model based on coronary artery angiography. The method comprises the following steps: acquiring a coronary artery scanning image of a patient; performing three-dimensional coronary artery space structure construction on the coronary artery image of the patient to generate a three-dimensional coronary artery space model; performing blood vessel diameter analysis on the three-dimensional coronary artery space model to generate coronary artery blood vessel diameter data; acquiring an X-ray angiography image of a patient; performing coronary artery vein structure construction on the X-ray angiography image of the patient to generate a three-dimensional coronary artery vein model; and performing blood vessel wall thickness analysis on the three-dimensional coronary artery vein model to generate coronary artery blood vessel wall thickness data. According to the method, multi-modal modeling is carried out by combining the coronary artery scanning image and the X-ray angiography image of the patient, anomaly analysis is carried out on the coronary artery, and the accuracy and reliability of coronary artery model reconstruction are improved.

The invention discloses a cardiovascular intervention catheter storehouse scheduling system based on demand analysis, and relates to the technical field of medical informatization, and the system comprises a data collection module which is used for obtaining an operation plan, a doctor identifier, a step sequence and an angiography image; the feature extraction module is used for generating a situation feature vector according to the contrast image; the standard deduction module is used for deducing subsequent steps and corresponding catheter sets; the selection probability calculation module is used for querying a doctor preference knowledge base in combination with the doctor identifier, the step code and the feature vector to obtain catheter selection probability distribution; the first judgment module is used for outputting a predicted catheter model if the catheter selection probability exceeds a first threshold value, otherwise, counting the catheter use frequency of the historical data of the doctor; the second judgment module is used for outputting the corresponding catheter model if the use frequency exceeds a second threshold value, otherwise, determining a predicted catheter model from the standard catheter set according to a rule; the accuracy and clinical suitability of catheter prediction can be improved.

The invention discloses a medical image optimization method and system based on vascular branch selective blurring. The method comprises the following steps: carrying out preprocessing and blood vessel enhancement on a three-dimensional angiography DICOM image; performing precise blood vessel segmentation by using an encoder-decoder network comprising a wide activation and residual cavity space pyramid module; identifying an interference branch which shields the target blood vessel structure at a specific working angle through blood vessel topology analysis; selective blurring repair is performed on the interference branches based on a Poisson equation and a bidirectional convolution LSTM to generate an optimized image which is visually unobstructed and keeps topological continuity. And a safety mechanism of virtual-real combined display and multi-angle plan planning is introduced, so that the reliability of surgical navigation is ensured. And finally, integrating the optimized 3D blood vessel model to a radiography system supporting real-time synchronization, and using the 3D blood vessel model as a road map. The clinical problem that the optimal working angle cannot be used due to blood vessel shielding can be effectively solved, and the precision and safety of an endovascular interventional operation are remarkably improved.

A surgical assistance device (1) is provided with: a true lumen information acquisition unit (14) that acquires three-dimensional position information of a true lumen present in a target blood vessel; a true lumen image generation unit (15) that acquires an angiographic image captured of the target blood vessel from the flat panel detector (21) disposed at the first imaging position, and generates a true lumen image of the true lumen indicating a position and orientation corresponding to the angiographic image using position information of the first imaging position and three-dimensional position information of the true lumen; and an image synthesis unit (16) that generates a synthesized image in which the angiography image and the true cavity image are synthesized, and outputs the synthesized image.

The invention provides an angiography CT (Computed Tomography) image-based early-stage pulmonary artery micro embolism detection method, which comprises the following steps of: extracting pulmonary parenchyma, and segmenting a small pulmonary blood vessel to obtain a pulmonary blood vessel tree; network weight is updated based on a neural evolution calculation method, and lung arteries and veins are separated; and obtaining a complete pulmonary artery tissue from a pulmonary artery and vein separation result, establishing a level set evolution model to enable the curve to be accurately evolved to the edge of a normal pulmonary artery tissue, and removing the normal pulmonary artery tissue to obtain a pulmonary embolism focus tissue so as to obtain a pulmonary embolism detection result. The method provided by the invention can accurately detect the micro embolism part at the early stage of pulmonary embolism, and has important clinical application value.

The invention discloses a blood vessel inner diameter correction method and device based on an X-ray total attenuation conservation principle and a storage medium, and belongs to the technical field of medical image processing. The core of the method is to discover and utilize the total net attenuation of a blood vessel filled with a contrast agent in an actual motion state and the total net attenuation of the blood vessel in an ideal static state to be kept in conservation. The method comprises the steps that an angiography image is acquired, and a target area and an initial inner diameter measuring line are determined; calculating the gray scale decline amount and the maximum value of each pixel of the line; on the basis of the conservation principle, the inner diameter of the blood vessel in an ideal state is inversely calculated through the formula that the inner diameter is corrected to be equal to sigma [(delta Ii / delta Imax) * Li]. Furthermore, based on the same principle, the method can be expanded and applied to correction of the two-dimensional contour of the target blood vessel. According to the method, errors caused by motion artifacts and resolution limitation are fundamentally compensated through a volume measurement method based on integration and distribution, and the method is particularly suitable for accurate measurement of severe stenosis blood vessels.

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.

A stenosis assessment method and device based on the intracranial digital subtraction angiographic (DSA) imaging, including acquiring the intracranial DSA imaging and extracting two planar images containing the target blood vessel from the DSA imaging, wherein the two planar images have different shooting angles. According to the two planar images, a 3D model of the target vessel is established. Based on the established 3D model of the target vessel and the DSA imaging, the hemodynamic simulation of the target vessel is performed. The disclosure realizes the functional assessment of intracranial vascular stenosis, improves the diagnostic accuracy, and provides certain assistance for neurologists to determine intervention means. The disclosure of noninvasive FFR technology in the assessment of intracranial vascular stenosis can only rely on angiography for functional assessment, saving the medical examination cost of patients. It has more convenient operation and higher repeatability.

The present invention relates to the technical field of medical image processing, and disclosed are a method and device for calculating blood flow at any position of a blood vessel tree. The method comprises: acquiring angiography image sequences, and performing structure extraction on images in the angiography image sequences to obtain two-dimensional blood vessel skeleton lines; performing three-dimensional reconstruction on the basis of the two-dimensional blood vessel skeleton lines to obtain a three-dimensional blood vessel model; determining a corresponding target blood vessel area on the basis of the three-dimensional blood vessel model, and calculating corresponding average blood flow in the target blood vessel area on the basis of transfer frame quantities corresponding to the angiography image sequences; reconstructing a reference blood vessel diameter on the basis of a corresponding blood vessel diameter in the target blood vessel area, and determining a blood vessel stenosis area on the basis of the blood vessel diameter and the reference blood vessel diameter; and calculating corresponding target blood flow at a target position in the target blood vessel area on the basis of the blood vessel stenosis area and the average blood flow. According to the present invention, blood flow at any position of blood vessels can be accurately calculated.

The invention relates to the technical field of medical image processing and interventional therapy assistance, and discloses an intubation fluorescent image feature learning system for hepatic artery chemoembolization. Comprising an image acquisition module which is configured to acquire a distortionless two-dimensional fluorescent blood vessel image in a hepatic artery chemoembolization super-selective intubation process; the control module is used for extracting surface geometric features of the blood vessel from the two-dimensional fluorescent blood vessel image; inputting the surface geometric features to a preset spatial reasoning model, and outputting a spatial distribution probability matrix of each blood vessel part; capturing a difference signal between the spatial distribution probability matrix and angiography feedback data in an actual intubation process in real time, and forming an iterative training data set to optimize the spatial reasoning model; and identifying a potential complex blood vessel region according to the spatial distribution probability matrix, generating an intubation path early warning signal, and generating guide parameters of X-ray release opportunity and dose based on the early warning signal so as to reduce radiation exposure.

The invention belongs to the technical field of DSA, and discloses a DSA platform-based multi-state real-time multi-mode image accurate fusion method. After an angiography image is collected on the basis of DSA equipment under the motion condition, accurate DSA blood vessel subtraction image enhanced display is achieved, meanwhile, hepatic artery extraction in a three-dimensional image in preoperative CT is completed, dynamic intelligent fusion of a precise anatomical structure in a preoperative multi-mode CT image and intraoperative local blood vessel development is combined, and the dynamic and intelligent fusion of the dynamic and intelligent fusion of the dynamic and intelligent fusion of the dynamic and intelligent fusion of the dynamic and intelligent fusion of the dynamic and intelligent fusion of the dynamic and intelligent fusion of the dynamic and intelligent fusion is achieved. The intrahepatic lesions and important blood vessels are accurately and visually displayed, operation planning is completed, fusion of three-dimensional information and two-dimensional DSA is utilized, and transvascular and percutaneous interventional operations are accurately guided.

The invention relates to the technical field of image processing, and discloses an interventional navigation method and system based on multi-modal image fusion. The method comprises the following steps: segmenting CT angiography data to form a three-dimensional vascular skeleton model, calculating MRI perfusion data to generate a vascular flow velocity field, and constructing a vascular geometric constraint matrix; performing diffusion reconstruction on the constraint matrix and the instrument position information, and outputting an instrument motion prediction track; estimating the postures of the tips of the X-ray perspective imaging instruments to form instrument-blood vessel space correlation features; safety navigation constraint parameters are generated through distance field calculation; and generating a real-time navigation instruction containing a propulsion distance and a rotation angle by adopting a path planning algorithm. The technical problems that in a traditional interventional navigation system, multi-modal image data fusion is insufficient, instrument motion prediction is inaccurate, and a safety constraint mechanism is incomplete are solved, and the precision, safety and real-time performance of interventional operation navigation are improved.