22 results about "Blood vessel structure" patented technology

The application discloses a percutaneous lung puncture path planning method and device based on lung segment level blood vessel structure constraint, and the method comprises the following steps: performing isotropic resampling, lung lobe segmentation and bronchial tree extraction on CT image data to generate a three-dimensional lung dissection model; inputting the three-dimensional lung dissection model into a lung segment semantic segmentation module to output a lung segment boundary; reconstructing the topological connection relationship between lung segment level blood supply arteries and drainage veins from the lung segment boundary to obtain a structured lung segment level blood vessel atlas; constructing a dynamic puncture risk field voxel map according to the structured lung segment level blood vessel atlas; sampling a plurality of candidate needle entry points in a surface feasible needle entry region to generate an initial path set in the three-dimensional lung dissection model; and weighting the path length, cumulative risk value, puncture angle penalty and high-density lung tissue volume according to a multi-objective optimization function to output a final puncture path. The application significantly improves the safety boundary and clinical applicability of percutaneous lung puncture.

This invention provides a deep learning-based intelligent analysis method for cardiovascular medical images, comprising the following steps: S1, heterogeneous data fusion and acquisition of multimodal medical images and physiological signals; S2, intelligent extraction and quantitative analysis of vascular structural features based on deep learning; S3, hemodynamic parameter modeling and risk region segmentation based on fused structural features; S4, texture feature mining and intelligent identification of lesion types in high-risk areas; S5, cardiovascular disease risk stratification prediction based on multi-dimensional feature fusion; S6, federated learning optimization and closed-loop update of the model. This invention's deep learning-based intelligent analysis method for cardiovascular medical images achieves, for the first time, heterogeneous fusion of medical images, millimeter-wave radar-PPG physiological signals, and clinical molecular data, and achieves precise spatiotemporal alignment through GPS-controlled crystal oscillators, overcoming the limitations of single image analysis and providing a more comprehensive feature foundation for subsequent feature extraction and risk prediction.

The application provides an aorta morphological feature automatic measurement and clinical auxiliary decision-making method and system based on artificial intelligence, which is suitable for three-dimensional medical image analysis of aorta and its main branches. The method comprises the following steps: image data acquisition and preprocessing, automatic blood vessel structure segmentation, center line extraction and key point positioning, multi-parameter automatic measurement, risk assessment and clinical auxiliary decision-making, data standardization output and system feedback optimization. The corresponding system comprises an image acquisition and processing module, a segmentation module, a center line extraction module, a parameter measurement module, an auxiliary decision-making module, a data output module and a verification and optimization module. Through a deep learning model and morphological calculation means, efficient identification and quantitative analysis of blood vessel structure are realized, and individualized risk suggestions and surgical planning are output based on statistical and machine learning models. The application improves the automation, standardization and intelligence level of blood vessel analysis, and enhances the clinical auxiliary decision-making ability under complex cases.

This invention relates to the field of image recognition, and more particularly to a method and apparatus for recognizing vascular structural features based on intravascular ultrasound images. The method includes the following steps: introducing an ultrasound catheter into a target blood vessel and performing a uniform retraction scan along the vessel axis to obtain a standard ultrasound image sequence; performing pixel-level segmentation and frame-by-frame contour feature calculation based on the standard ultrasound image sequence to generate contour structural feature parameters for different frames; performing vascular axial direction position analysis on the standard ultrasound image sequence to generate three-dimensional pose information of the vascular contour for each frame; identifying key contour feature points and modeling discrete point clouds based on the three-dimensional pose information to construct a three-dimensional mesh model; and performing surface smoothing filtering and parameter constraint adjustment on the three-dimensional mesh model based on the contour structural feature parameters to construct a global three-dimensional model. This invention improves the accuracy of vascular structure recognition and visualization analysis capabilities, providing a direct visual representation of vascular structures.

The embodiment of the specification provides a blood vessel blood oxygen saturation calculation method based on a multispectral fundus image. The method introduces blood vessel skeleton extraction and blood vessel topology graph construction, and realizes fine description of the blood vessel structure. Based on the blood vessel topology graph, the blood vessel radius is adaptively calculated, the positioning accuracy of the blood vessel is improved, and a more accurate pixel value basis is provided for subsequent blood vessel inside and outside pixel value calculation. The method introduces a light intensity ratio compensation mechanism. In the 548nm optical density calculation, the 605nm blood vessel outside pixel value is converted into equivalent 548nm incident light intensity through the pre-calibrated light intensity ratio, the difference in reflection characteristics of different wavelengths of the tissue is eliminated, the accuracy of the optical density calculation result is improved, and the accuracy of the blood oxygen saturation calculation result is improved.

The application discloses a kind of human peripheral blood vessel photoacoustic three-dimensional imaging device and imaging method thereof, belong to blood vessel imaging field.The application provides detailed blood vessel structure and blood flow dynamic information by high resolution and functional monitoring ability of photoacoustic imaging, promote early identification and treatment effect evaluation to common pathological changes such as diabetic foot and peripheral arterial disease;Meanwhile, the application adopts mechanical system, and the detection front end of higher quality can be carried and stably operated, to obtain better photoacoustic imaging result;The application has highly stable precision scanning imaging mode, and various imaging modes are convenient for clinical application;Through the arrangement of imaging tank and its lifting structure, it is ensured that the switching of imaging mode can be applied in limited space, so as to be suitable for gantry type three-dimensional mobile device layout.The application is expected to promote the portability of equipment, reduce equipment development cost, be widely applied in clinical practice and community medical treatment, and improve disease management level.

The application discloses a kind of based on frequency domain enhancement's retinal blood vessel segmentation method, it is related to retinal blood vessel segmentation technical field, the method includes: the input retinal image is preprocessed to enhance blood vessel structure information;The spatial domain feature of image is extracted by multilevel encoder;Dynamic frequency domain enhancement processing is carried out to spatial domain feature, including using learnable Gaussian high-pass filter and K groups learnable complex Fourier base weighted fusion to generate adaptive frequency domain mask to enhance blood vessel edge high-frequency component;Frequency domain enhancement feature and spatial domain feature are input into cross-domain routing attention module and are fused;Key feature position is filtered using double-layer routing mechanism and sparse attention is calculated;Blood vessel segmentation result is output by the decoder upsampling fusion feature and output blood vessel segmentation result.The application is enhanced by learnable Gaussian high-pass filter adaptive blood vessel edge frequency domain feature, combined with spatial domain feature to carry out cross-domain routing attention fusion, realizes high-precision, high-efficiency blood vessel segmentation under the improvement U-Net architecture.

The application discloses a kind of free skin flap postoperative nursing scheme evaluation and early warning method based on multi-modal monitoring data fusion, it is related to intelligent medical care technical field, for solving the problem that existing monitoring cannot distinguish vascular pathological crisis and nursing environment interference.First, a multi-dimensional time-varying state matrix containing physiological drive and nursing environment characteristics is constructed, realizing the time sequence alignment of heterogeneous data;Subsequently, the pressure-flow conduction characteristics are analyzed, and the blood flow conduction efficiency index reflecting the inherent patency of blood vessels is extracted;At the same time, a physical gain mapping is established based on nursing parameters, and the theoretical target perfusion trajectory under the current nursing state is deduced;Finally, the dynamic residual vector is calculated and combined with the conduction efficiency index for joint determination, accurately identifying vascular structural occlusion and functional inhibition of nursing program, achieving accurate tracing of postoperative crisis and dynamic evaluation of nursing program.

The application relates to the technical field of digital pathological image analysis, and particularly discloses a hepatocellular carcinoma blood vessel pattern analysis system and application thereof. The hepatocellular carcinoma blood vessel pattern analysis system comprises an image acquisition module, a tumor region detection module, a blood vessel segmentation module, a blood vessel subtype classification module and a blood vessel pattern analysis module. The blood vessel subtype classification module is used for identifying blood vessel subtypes in a blood vessel binary mask image. The blood vessel pattern analysis module is used for identifying a blood vessel pattern, and the hepatocellular carcinoma is classified and prognosis evaluation is performed according to the blood vessel pattern. The system constructed by the application can realize automatic identification of blood vessel structures and subtypes in hepatocellular carcinoma tissues, and can stably and accurately complete hepatocellular carcinoma classification and determination based on the hepatocellular carcinoma blood vessel pattern, thereby solving the technical bottlenecks that the hepatocellular carcinoma blood vessel evaluation in the prior art depends on artificial interpretation, is highly subjective, has poor consistency, and is difficult to realize quantitative analysis of blood vessel morphological characteristics, and lacks precise hepatocellular carcinoma classification and prognosis evaluation based on the blood vessel pattern.

The application relates to the technical field of medical devices, in particular to a bionic liver ablation training phantom, wherein a bionic liver tissue base material adopts a double-network hydrogel system formed by polyvinyl alcohol and acrylamide, the conductivity and the sound velocity are adjusted by adding iodized salt, and the acoustic impedance and the sound attenuation coefficient are adjusted by adding barium sulfate powder; the bionic tumor lesion contains a heat-sensitive developing system and an ultrasonic imaging regulator, so that the bionic tumor lesion presents different echo characteristics from normal liver tissue under ultrasonic waves and can permanently change color after ablation to directly show the heat field range; and the bionic blood vessel structure is made of a three-dimensional printing TPU hose. The phantom is stable in physical and chemical properties, can be stored for a long time and used for multiple times, the raw materials are common chemical materials, the cost is low, the preparation process is simple, and the phantom is suitable for large-scale production.

The invention provides an automatic virtual coronary intervention planning method based on multi-target heuristic optimization, and the method carries out coronary stent layout planning based on coronary CT or angiography sequence data, and comprises the steps: obtaining the current coronary CT or angiography sequence data, generating a coronary vessel structure model according to a coronary cavity surface and a center line point set, and carrying out coronary stent layout planning according to the coronary vessel structure model. Carrying out topology analysis and smoothing processing on the coronary blood vessel structure model to generate a finite element grid; generating performance feedback indexes according to the finite element mesh and a preset hemodynamic simulation model, wherein the performance feedback indexes comprise blood pressure distribution, a flow velocity field and a fractional flow reserve value; determining an optimal region of a strategy solution set according to the blood pressure distribution, the flow velocity field and the fractional flow reserve value; and determining an optimal individualized coronary intervention planning scheme according to the optimal region and a preset constraint rule, so that the search efficiency and the calculation speed are improved on the premise of ensuring the simulation precision, and the decision-making efficiency and the operation effect are improved.

The present invention relates to image processing of angiograms. A device for enhancing angiograms is provided. The device comprises a data input, a data processor, and an output interface. The data input provides at least one angiographic image showing a vascular structure of interest comprising a plurality of vessel branches. The data processor is configured to determine at least one branch of interest from the angiographic image, to segment the angiographic image for identifying possible branches of the vascular structure, to select branches based on the identified possible branches and the determined branch of interest, to estimate attenuation values of the selected branches, and to subtract at least a predetermined part of the estimated attenuation values from the angiographic image to generate a corrected angiogram. The output interface is configured to provide the corrected angiogram.

The application relates to the field of artificial intelligence, and discloses a coronary heart disease prediction model generation method based on artificial intelligence, which comprises the following steps: acquiring dynamic physiological time series data and static blood vessel structure data of a test object; respectively extracting multi-scale dynamic physiological representation and topological blood vessel structure representation; performing cross-modal space-time alignment and feature interaction through a bidirectional cross-attention mechanism to generate fusion representation; and training a coronary heart disease risk prediction model based on the fusion representation. The method comprises the following modules: multi-source data acquisition, dynamic physiological feature coding, blood vessel structure graph modeling, cross-modal feature fusion, and prediction model training. The application synchronously integrates dynamic physiological time series data continuously collected for a long time and high-resolution coronary artery structure image data, and constructs a coronary heart disease risk assessment system in dual dimensions of physiological function and anatomical structure.

The application discloses a photoacoustic probe and a preparation method and application thereof, and relates to the technical field of biomedicine. The application provides application of the photoacoustic molecular probe connected with a target unwinding collagen in preparation of products for detecting or assisting in detecting cardiovascular diseases, or in preparation of products for predicting or assisting in predicting aneurysm rupture risk. Experimental results prove that the photoacoustic probe connected with the target unwinding collagen can be used for non-invasive photoacoustic ultrasonic imaging detection of vascular structure function disorder diseases such as aneurysm, and can realize non-invasive early detection and rupture risk assessment of abdominal aortic aneurysm, coronary aneurysm, carotid aneurysm and the like, thereby providing a powerful tool for early intervention and precise treatment of cardiovascular diseases.

The application relates to the technical field of medical image intelligent analysis, and discloses a prostate cancer early screening model and a construction method thereof. The method receives original image data from multiple sources in parallel, and obtains a candidate image set after quality evaluation and screening. The candidate image is subjected to layer-by-layer structure decomposition, and a background layer, a tissue layer and a blood vessel structure layer are separated. Structure features of the tissue layer and the blood vessel structure layer are extracted, and are compared with corresponding standard tissue feature libraries and standard blood vessel feature libraries, and a primary risk feature group is formed according to the differences. The feature group is subjected to time sequence simulation evolution, a simulation feature state at a future time point is generated, and is coupled with a current state to construct a dynamic risk feature map. The dynamic risk feature map is used to search for a path with the highest matching degree in a preset risk screening path, and a final risk decision mark is generated. The application realizes decoupled analysis of image components and dynamic risk evaluation.

The application discloses a retinal blood vessel identification method, system, device and medium, the method comprises the following steps: acquiring a retinal blood vessel image; identifying the retinal blood vessel image according to a retinal blood vessel model to obtain a retinal blood vessel identification result; wherein the retinal blood vessel model is obtained through the following steps: acquiring and preprocessing an original retinal image set to obtain a first retinal image set; performing feature extraction processing on the first retinal image set to obtain a second retinal image set; performing adaptive clustering processing on the second retinal image to obtain a clustering identification result; updating the retinal blood vessel model according to the clustering identification result to obtain an updated retinal blood vessel model. The method can effectively guarantee the integrity and connectivity of the retinal blood vessel structure, effectively improve the anti-noise performance and identification accuracy of the retinal blood vessel identification, and improve the detection sensitivity of the low-contrast small blood vessel structure. The application relates to the technical field of image processing.

This invention belongs to the field of medical image processing and analysis technology, specifically a three-dimensional vascular registration method for digital subtraction angiography (DSA) and magnetic resonance angiography (MRA). The invention includes: preprocessing DSA and MRA images to initially align the skull and eliminate intensity differences between images; segmenting blood vessels in the DSA and MRA images to remove skull and other brain tissue from the original images; initializing a three-dimensional vascular map by converting the blood vessels in the original images into a vascular map model; performing rigid registration of the blood vessels to initially align the vascular structures in physical space; and performing non-rigid registration of the blood vessels to correct vascular deformation. This invention can achieve high-precision alignment of DSA and MRA in three-dimensional space, ensuring the consistency of vascular structures and providing more accurate image support for the diagnosis, preoperative planning, and postoperative evaluation of clinical vascular diseases.

The application discloses a medical image optimization method and system based on blood vessel branch selective virtualization. The method comprises the following steps: pre-processing and blood vessel enhancement are performed on a three-dimensional angiography DICOM image; an encoder-decoder network containing a wide activation and residual hollow space pyramid module is used for accurate blood vessel segmentation; through blood vessel topology analysis, interference branches that shield target blood vessel structures under a specific working angle are identified; based on a Poisson equation and a bidirectional convolution LSTM, selective virtualization repair is performed on the interference branches to generate an optimized image that is visually unshielded and maintains topological continuity. A safety mechanism of virtual-real combined display and multi-angle preplan is introduced to ensure the reliability of surgical navigation. Finally, the optimized 3D blood vessel model is integrated into a contrast system supporting real-time synchronization and used as a roadmap. The application can effectively solve the clinical problem that the best working angle cannot be used due to blood vessel shielding, and significantly improves the accuracy and safety of intravascular intervention surgery.

The utility model relates to a low -cost magnetic erection device, and the device promotes the production of nitric oxide through endothelial nitric oxide synthase (eNOS) from endothelium, that is, the innermost layer of blood vessel structure, does not need contact and does not contain chemical substances when applying in vitro, increases the blood circulation of the tissue of application area, simultaneously provides the possibility of repeated use and portable use through its in vitro, promotes the blood vessel expansion of application area through pulsed electromagnetic field (PEMF), increases the synthesis of tissue growth factor (such as vascular endothelial growth factor), does not cause painful irritation, and can adjust power, frequency and duration.

The utility model relates to hemodialysis technical field especially, it is a kind of pipeline connecting device of immediate wear type artificial blood vessel, including subcutaneous tissue layer, the skin layer of being in the upper layer of subcutaneous tissue layer, the venous blood vessel and arterial blood vessel being arranged between subcutaneous tissue layer and skin layer and the artificial blood vessel being established between venous blood vessel and arterial blood vessel. In the utility model, the original artificial blood vessel structure is improved scientifically and rationally, venous transfusion port, arterial transfusion port, oval puncture bevel and rubber septum are arranged on artificial blood vessel, artificial blood vessel can be embedded between subcutaneous tissue layer and skin layer, and skin puncture hill, which is convenient for puncture needle to puncture and position, can be formed on skin layer, effectively reduce the risk problems such as surgical trauma, puncture risk, catheter infection, central vein stenosis and even occlusion of hemodialysis process of hemodialysis patient, thereby improve the security and stability of actual hemodialysis use.

The application relates to the technical field of medical health, and discloses a construction method of a blood vessel lesion prediction model, which comprises the following steps: extracting blood vessel lesion features of a subject from a blood vessel image to construct a blood vessel lesion heat map of the subject; creating a blood vessel shape calculation layer of the blood vessel lesion based on blood vessel geometry and blood vessel structure; extracting heterogeneity features of the subject, and setting a heterogeneity classifier of the subject; analyzing a blood vessel lesion trend of the subject, and creating a blood vessel lesion risk stratification of the subject; and combining the lesion heat map, the blood vessel shape calculation layer, the heterogeneity classifier and the blood vessel lesion risk stratification to construct a blood vessel lesion prediction model of the subject. The application can accurately analyze the interaction relationship between blood vessel lesion indexes and improve the prediction accuracy of the blood vessel lesion.