136 results about "Tissue architecture" patented technology

The invention discloses an ultrasonic image denoising method based on variational mode decomposition and local space sparse fusion, which comprises the following steps of: firstly, adaptively optimizing key parameters of variational mode decomposition by using a grey wolf optimization algorithm to realize stable and efficient decomposition of an ultrasonic image; then, classifying the modal components according to the structural features of the modal components, and implementing differentiated denoising strategies for different types of modals to separate noise and reserve useful information; after modal reconstruction, a sparse expression method based on local space information is further introduced, according to the method, accurate boundary detection is carried out through gradient vector flow and gray scale proportion analysis, self-adaptive partitioning is carried out on an image according to boundary information, and finally sparse reconstruction is carried out through double dictionaries trained for different areas. According to the method, speckle noise in the ultrasonic image can be effectively suppressed, and meanwhile, the capability of keeping the edge and detail information of a tissue structure is remarkably improved, so that the ultrasonic image with higher quality is obtained.

The utility model relates to the technical field of fixation and preservation of biological tissue samples, and provides an embedding mold for multiple frozen tissues, which comprises a base, a plurality of clamping pieces, a plurality of clamping pieces and a plurality of clamping pieces, and is characterized in that the top surface is provided with a pair of centrosymmetric supporting blocks; the sleeve is detachably arranged outside the pair of supporting blocks in a sleeving manner; wherein the pair of supporting blocks are arranged at an interval of 180 degrees, and the outer side walls of the supporting blocks are attached to the inner side wall of the sleeve in a transition fit mode; the sleeve is as high as the supporting block, and an accommodating cavity is defined by the inner side wall of the sleeve and is used for embedding the plurality of strip-shaped frozen tissue blocks in a vertical form. The containing cavity formed in the sleeve is changed into a columnar shape with enough depth from an existing flat shape with limited depth, the problems that the tissue structure is incomplete and an OCT embedding medium overflows are directly solved, the edge of a tissue combined block is smooth, slicing is facilitated, meanwhile, a plurality of strip-shaped frozen tissue blocks are embedded in a vertical mode, and the working efficiency is improved. The height of the tissue block is unified, the size of the tissue block is fixed, and the problems that sample loss is large and tissue arrangement is too close to the edge are solved.

The invention discloses a laparoscopic surgery image enhancement and real-time auxiliary system, and relates to the technical field of medical image processing and intelligent auxiliary surgery. According to the laparoscopic surgery image enhancement and real-time auxiliary system, a laparoscopic image flow is obtained and cleaned through the video input and preprocessing module, image enhancement processing is carried out through a deep learning model, then spatial position features of a tissue structure and an instrument are extracted, and a structure recognition index and a spatial safety index are analyzed; according to the invention, through cooperative work of the image preprocessing module and the depth image enhancement model, brightness compensation, edge enhancement, denoising, smoke suppression and other operations are performed on the laparoscope image stream, the depth model is utilized to extract multi-scale image features and reconstruct details, and an enhanced video image stream is generated; therefore, the intraoperative abdominal cavity structure and instrument boundary is clearer, the positioning judgment precision of a doctor is remarkably improved, and the misjudgment risk caused by image blurring is reduced.

The invention provides a regional anesthesia puncture path planning method and system under ultrasonic guidance, and relates to the technical field of ultrasonic image.According to the regional anesthesia puncture path planning method and system, dynamic motion information of a tissue structure is obtained by collecting ultrasonic image data of a target region and conducting motion analysis, and electrocardiosignals are synchronously collected to determine heart beat time phase information; determining a vascular movement mode based on the two, learning a time change rule by using a long-short-term memory network, and establishing an association relationship between a vascular spatial position and a heart beat phase; constructing a motion prediction model to predict the future motion trend of the blood vessel, and fusing the respiratory motion information to correct to obtain the blood vessel motion information; and finally, a safe puncture window is calculated according to the information, a regional anesthesia puncture path is planned, vascular movement prediction and safe puncture window calculation based on vascular movement rule learning and breathing correction in regional anesthesia under ultrasonic guidance can be achieved, and then the puncture path is precisely planned.

The invention relates to the technical field of medical image processing and three-dimensional reconstruction, and particularly discloses a reconstruction and analogue simulation method based on a cardiac image. The method comprises the following steps: firstly, preprocessing an input CT or MRI medical image, and automatically segmenting a heart multi-tissue structure by using an nnUNetv2 model, including a plurality of anatomical regions such as atrium, ventricle, myocardial tissue and blood pool; and then performing topology repair, smoothing processing and label resampling on the segmentation result to obtain a three-dimensional label body with a continuous structure and a complete boundary. And based on the optimized tag body, constructing a heart three-dimensional surface model by adopting a Marching Cubes algorithm, and generating a multi-material volume grid suitable for finite element analysis. According to an electrode position and a radio frequency parameter set by a user, a radio frequency ablation simulation model based on a Pennes biological heat conduction equation and an Arrhenius model is established, a temperature field and a tissue thermal damage range are calculated, and a simulation result is displayed in a three-dimensional mode in an overlapping mode. According to the method, the integrated process from medical image automatic segmentation to heart three-dimensional reconstruction and thermal simulation is realized, the segmentation precision, the modeling efficiency and the simulation reliability are improved, and the method can be applied to application scenes such as surgical planning, preoperative evaluation and medical teaching.

The invention discloses a multi-layer heterogeneous network unicellular organism network inference method based on meta-path enhancement, which mainly comprises a gene regulation knowledge base enhanced multi-layer heterogeneous network construction module for integrating an external gene interaction network and multiple omics data such as scRNA-seq, scATAC-seq, ST and the like; constructing a single-cell multi-omics multilayer heterogeneous network containing cell-cell, cell-gene and gene-gene relationships, and fusing spatial constraints to consider cell positions and tissue structures; and the feature enhancement module based on the meta-path explores complex semantics of the network by designing a multi-hop meta-path mode, designs an adaptive multi-view learning framework and a multi-round enhancement mechanism, and optimizes feature representation by using cell-gene interaction and cross-modal attention fusion. The unicellular biological network can be effectively deduced, the deduction accuracy and biological interpretation are remarkably improved, the method plays an important role in understanding the cell biological process, developing and treating diseases and the like, has good expandability, and can further integrate multi-modal omics data such as proteomics and metabonomics.

The invention provides a pathological image analysis method and device based on multi-instance learning, equipment and a storage medium, and the method comprises the steps: receiving a lung pathological section image, segmenting the lung pathological section image into a plurality of 256 * 256 pixel image blocks, and screening and reserving effective image blocks containing a tissue structure; extracting a high-dimensional feature vector of each effective image block by using a self-supervised pre-trained deep neural network on the large-scale dyeing pathological image; the features are input into a multi-branch attention module containing 15 parallel branches, self-attention, cross-attention and global attention mechanisms are executed respectively, and local spatial dependence, cross-image block similarity and global relevance are modeled; and carrying out weighted aggregation on the basis of the processed attention weight to generate a global feature of the slice image, outputting a pathological category through a classification network, and supporting heat map visualization and feature clustering analysis. According to the method, unlabeled region information is effectively utilized, and the pathological classification precision and the model generalization ability are improved.

The application discloses a cancer survival prediction method and device based on whole-slice pathological images, and relates to the technical field of medical artificial intelligence and digital pathological image analysis. The method comprises the following steps: acquiring whole-slice pathological images and patient survival information, and performing pretreatment; performing cell detection on the whole-slice pathological images to obtain cell structure data; dividing the whole-slice pathological images into a plurality of image regions, and determining regions of interest; screening the cell structure data in each region of interest to construct a cell subset; sorting the cell structure data according to the distribution relationship of cells in space to construct a cell structure sequence; constructing a cell structure modeling model, performing feature modeling on the cell structure sequence, and obtaining tissue structure features capable of representing the microstructure of tumor tissues; and inputting the tissue structure features into a survival prediction model to predict the survival risk of the patient. The application can improve the accuracy and stability of cancer survival prediction.

The invention discloses an ultrasonic shear wave elastography-based intrameniscus tearing quantitative evaluation method and system, and relates to the technical field of computer-aided diagnosis. The method is used for solving the problem of insufficient quantification of meniscus tearing detection. The method comprises the following steps: firstly, fixing a knee joint at a preset buckling angle, exciting shear waves along an annular fiber direction and a vertical direction, and collecting ultrasonic radio-frequency signals of an affected side meniscus and an uninjured side meniscus in different load states; then, a three-dimensional anisotropic elastic atlas is constructed based on the shear wave propagation velocity field, and spatial elastic distribution characteristics of the tissue are obtained; thirdly, calculating an elastic continuity index, a spatial variation coefficient and an abnormal region morphological parameter, and quantitatively representing the continuity and local tearing characteristics of the tissue structure; and finally, inputting the multi-dimensional features into a multi-branch neural network, fusing the features through a cross-branch attention mechanism, and outputting a meniscus tearing quantitative evaluation value, thereby realizing intelligent and objective evaluation of the tearing degree, and providing a basis for clinical diagnosis and postoperative rehabilitation.

The invention provides an ultrasonic plane wave multi-mode cooperative imaging method and system, and the method comprises the steps: controlling an ultrasonic probe to execute shear wave elastic imaging and sound attenuation imaging of which the mechanical index is equal to or greater than a first threshold value based on a multi-level voltage control scheme; and executing super-resolution imaging with the mechanical index smaller than or equal to a second threshold value after the super-resolution imaging is completed. The method comprises the following steps: acquiring a sound attenuation coefficient graph generated in a sound attenuation imaging process, and respectively acquiring a first super-resolution graph without contrast agent perfusion, a second super-resolution graph with contrast agent perfusion and a tissue elasticity graph generated in a shear wave elasticity imaging process based on an ultrafast plane wave technology; performing post-processing on the collected first super-resolution graph to generate a probability density graph of the tissue structure, and performing post-processing on the collected second super-resolution graph to generate a microbubble tracking speed graph; and carrying out cooperative imaging on the tissue elasticity map, the sound attenuation coefficient map, the probability density map and the velocity map. The imaging comprehensiveness and accuracy are improved, and early lesion diagnosis is facilitated.

Apparatus, systems, and methods are provided for localizing lesions within a patient's body, e.g., within a breast. The system may include one or more markers implantable within or around the target tissue region, and a probe for transmitting and receiving electromagnetic signals to detect the one or more markers. During use, the marker(s) are into a target tissue region, and the probe is placed against the patient's skin to detect and localize the marker(s). A tissue specimen, including the lesion and the marker(s), is then removed from the target tissue region based at least in part on the localization information from the probe.

The application provides a multi-modal tissue segmentation method and a surgical navigation system, and the method comprises the following steps: inputting three-dimensional medical images of multiple modes into corresponding deep learning network models respectively for segmentation to obtain corresponding three-dimensional segmentation results; registering the three-dimensional medical images of each mode to obtain a registration relationship; and according to the registration relationship, combining the three-dimensional medical images of each mode to weight and fuse the three-dimensional segmentation results of each mode according to preset weights of each type of tissue. The application trains a segmentation model for each mode of medical image, each deep learning model has stronger segmentation capability for the medical image of the corresponding mode, and has higher segmentation precision; different types of medical images are respectively designed with preset weights (mode weights) of each type of tissue, and the segmentation results are fused according to the mode weights in the fusion process, so that the tissue structure characteristics are more fully reflected, and the segmentation precision is improved.

This invention discloses a coherent electrical stimulation method for idiopathic scoliosis combined with exercise therapy, belonging to the field of electrical stimulation methods for idiopathic scoliosis. It aims to address the problem of how to dynamically adjust stimulation parameters based on individual differences to improve treatment efficacy. The method includes acquiring raw image sequences of the patient's spine through MRI scans, preprocessing the raw image sequences to construct a three-dimensional geometric model of the spine, configuring simulated electrical property parameters for the tissue structures, and then adding coherent electrical surface electrodes to the model. The electrode placement area on the three-dimensional geometric model of the spine is initially defined, and a coherent electrical stimulation signal is generated using a function generator. A comprehensive evaluation index value is calculated through finite element analysis to dynamically adjust the coherent electrical stimulation signal. Based on the coherent electrical stimulation signal parameters and its comprehensive evaluation index value, a coherent electrical stimulation scheme is determined, and ultrasound-guided technology is used to locate the electrode positions and implement coherent electrical stimulation therapy.

The present application relates to a kind of coke reaction after strength prediction method of comprehensive optical tissue and pore structure characteristics, comprising:1) optical tissue structure analysis;2) pore structure parameter analysis;3) comprehensive influence analysis and the establishment of CSR prediction formula.The present application uses microcosmic optical tissue structure and pore structure characteristic index to predict CSR, compared with the conventional prediction method using macroscopic index, the workload needed for microcosmic index determination is greatly reduced, thereby reducing the coke oven test operation and response time in field, improve efficiency and reduce cost;In addition, microstructure can essentially reveal the change rule of coke performance, according to the prediction result, coal blending structure can be adjusted, more widely applicable, the prediction result is more accurate.

The present disclosure relates to an apparatus for optoacoustic sensing of tissue features, such as tissue architecture, morphological information, function, physiology and / or molecular information about biomolecules, in particular metabolites, in a biological tissue (1) and a corresponding method. The apparatus comprises at least one illumination device (2) configured to illuminate the tissue (1) with first electromagnetic radiation (3) exhibiting one or more wavelengths or wavelength ranges in a first spectral range, at least one detection device (5) configured to detect, in response to illuminating the tissue (1) with the first electromagnetic radiation (3), at least one first optoacoustic signal corresponding to ultrasonic waves (6) emanating from a region of interest (ROI) in the tissue (1), and a processor (7) configured to determine, based on the first optoacoustic signal, at least one first parameter characterizing a first tissue feature of interest in the region of interest (ROI).

The invention relates to the technical field of image data processing, and discloses a pathological detection device and method based on image recognition and analysis. According to the method, cell nucleus and gland structures are identified by acquiring a full pathological image; constructing a cross-scale heterogeneous graph containing a cell nucleus node, a gland node, a same-scale edge and a cross-scale edge based on an identification result; inputting the heterogeneous graph into a graph neural network for coding to obtain node representation fused with cross-scale context information; in the training stage, part of gland node features are randomly shielded, and self-supervised learning is carried out by predicting shielded features; in a detection stage, a prediction error of each gland node is calculated as a structural anomaly index, and a structural anomaly thermodynamic diagram is generated. According to the method, accurate quantification of tissue structure heterogeneity is achieved, the technical problems that an existing method neglects tissue structure semantics and depends on expensive labels are solved, and the method has the advantages of being high in detection accuracy, high in interpretability and good in clinical applicability.

The invention discloses a high-polysaccharide dendrobium officinale variety germination period directional screening cultivation method, and belongs to the technical field of tissue culture. The invention provides a high-polysaccharide dendrobium officinale variety germination period directional screening cultivation method aiming at the problems that existing dendrobium officinale germplasm is mixed and the polysaccharide content is unstable. According to the method, the concentration of a periodate solution adopted for acidolysis treatment is remarkably reduced, the acidolysis time is shortened, a chromogenic reaction is achieved outside the protocorm, the situation that epidermal cells of the protocorm are excessively damaged and a coloring agent enters the protocorm to cause tissue structure change is avoided, and it is guaranteed that the structure of dendrobium officinale is complete and the shape of dendrobium officinale is stable; meanwhile, the dyeing time is shortened, rapid and lossless identification of the dendrobium officinale high-polysaccharide germplasm in the protocorm stage is achieved, the breeding period is remarkably shortened, and the screening accuracy and efficiency are improved. The cultivated high-polysaccharide dendrobium officinale variety shows consistency and stability in the aspects of polysaccharide content and agronomic traits.

According to the X-ray imaging method and the X-ray imaging device, a radiation image of the chest is obtained, a first image with the same tissue structure as the radiation image is generated based on the radiation image of the chest, the fracture position of a rib in the first image and / or the position of one or more ribs with fractures in the first image are / is marked, and a marked image is obtained; displaying the radiation image and the marking image; therefore, a user can directly observe the fracture position of the rib through the displayed radiation image and the marked image, and the diagnosis efficiency and accuracy are greatly improved.

The invention relates to a parameter image construction method and device, equipment, a storage medium and a program product. The method comprises the following steps: acquiring a PET dynamic image; the PET dynamic image comprises a target organization structure; generating analysis parameters and to-be-input data according to the PET dynamic image; the analysis parameters comprise an image construction model, a target frame time range and an input function of a target organization structure; the to-be-input data comprises a PET original image and dynamic data of a heart area, or the to-be-input data comprises a PET dynamic image; and constructing a parameter image corresponding to the PET dynamic image according to the analysis parameter and the to-be-input data. By automatically determining the accurate analysis parameters and the to-be-input data, the situation that the effect of the parameter image is not ideal due to the fact that a user is not familiar with the influence of the analysis parameters on generation of the parameter image can be avoided, and therefore the accurate parameter image corresponding to the PET dynamic image can be constructed.

The present disclosure provides methods and apparatus for evaluating tissue structure in damaged or healing tissue. The present disclosure also provides methods of identifying a patient at the onset of risk of pressure ulcer or at risk of the onset of pressure ulcer, and treating the patient with anatomy-specific clinical interventions selected, based on spectral imaging (SI). The present disclosure also provides methods of stratifying groups of patients based on risk of wound development and methods of reducing incidence of tissue damage in a care facility. The present disclosure also provides methods to analyze trends of SI intensities to detect tissue damage before it is visible, and methods to compare bisymmetric SI intensities to identify damaged tissue.

The invention relates to the technical field of brain stimulation, in particular to a brain stimulation system and method based on optical genetic regulation, and the system comprises a target screening module, an illumination path adjustment module, a neural response extraction module, a regulation trend recognition module and an irradiation parameter linkage module. According to the method, multiple index evaluations are constructed according to the three-dimensional characteristics and discharge frequency information of a neuronal synaptic output path in a target brain region, target neurons with main path peak control capability are screened, anisotropy quantization parameters are calculated according to scattering characteristic differences of tissue structures in an illumination propagation path, and an optical fiber incident angle is adjusted in real time; according to the method, local illumination is utilized to realize directional coverage of specified neurons, the response change trend is identified and regulated by analyzing the maximum amplitude of frequency shift and the number of times of direction reversal, the illumination intensity, pulse width and period parameters are automatically adjusted in combination with response categories, dynamic tuning of the stimulation process is realized, and the precision and the adaptive ability of nerve stimulation are improved.

The invention discloses a burn injury assessment method based on an imaging technology, and relates to the technical field of medical image.The method comprises the steps that multi-angle imaging is conducted on a burn area through a medical photography device, an auxiliary image is constructed, a binary mask is generated, and the binary mask is mapped to an original image to obtain a burn area image; performing gradient analysis and gridding processing on the burn area image to obtain a gradient direction angle theta and a direction probability distribution value fb, and quantifying and integrating tissue direction characteristics to form a structured index set; carrying out instability state analysis on the burn tissue structure to form a two-dimensional confusion degree matrix and finishing structure risk grading; carrying out evolution evaluation by calculating the relative variation of two unstable state analysis results; and finally, mapping the risk level result to the original image in a pseudo-color form. According to the method, a technical means based on imaging data is provided for grading judgment and evolution observation of burn injury conditions through quantitative analysis and time sequence comparison evaluation of tissue structure direction characteristics.

This invention provides an ultrasound imaging method, apparatus, electronic device, storage medium, and program product. The method includes: acquiring region of interest (ROI) data and tissue data of a target tissue, wherein the ROI data and tissue data are acquired using different ultrasound imaging methods; rendering the tissue data to obtain a first rendered image; rendering the tissue data and the ROI data to obtain a second rendered image; and fusing the first and second rendered images to obtain a fused image. This fused image better presents the relative spatial position of the ROI within the entire tissue structure. Furthermore, the fused image has a stronger sense of depth, higher smoothness and realism, significantly improving the user experience.

The application discloses a monocular endoscope-oriented polarization three-dimensional imaging method and device. The method comprises the following steps: firstly, a polarization three-dimensional imaging data set suitable for a medical endoscope scene is constructed; then, based on the polarization characteristics of the tissue structure in the endoscope environment, a neural network model fusing a double-domain cross attention mechanism is designed and constructed. The network is effectively trained by introducing a fusion loss function, and the trained model is saved. Subsequently, the tissue image collected by the endoscope in real time is input into the trained model, and the normal vector information of the tissue surface is output. The normal vector solving method proposed by the application has the advantages of high precision and strong robustness in combination with the physical principle of deep learning and polarization imaging, and is suitable for complex endoscopic medical scenes.

The invention discloses an ablation catheter which comprises a catheter body which comprises a head end electrode section, a transition connection section, a bendable section, a main body section and a handle which are sequentially connected from far to near, and the catheter body is provided with an axially-through guide wire passage; the pull wire system comprises at least two pull wires, the near end of each pull wire is connected with the handle, the far end of each pull wire is connected with the head end electrode section or the transition connection section, and the at least two pull wires can be driven to control the bendable section to bend in different directions; therefore, the ablation catheter can be guided in place in a tissue structure through the guide wire, the operation control difficulty is reduced, the attaching performance can be improved through bending control of the handle, damage to blood vessels is reduced, and the ablation effect is improved.

The invention discloses a cardiovascular image processing method and electronic equipment. Belongs to the technical field of cardiovascular image processing. The method comprises the following steps: acquiring a first mask corresponding to a cardiovascular structure according to a first image acquired in a TOF mode; acquiring a second mask corresponding to the tissue structure according to a second image acquired in the T1 mode; based on a cross attention network, obtaining spatial relevance between the tissue structure and the cardiovascular structure in the first image and the second image; the cardiovascular structure and tissue are spatially aligned based on spatial relevance; and determining anomalies between the continuous frames based on the continuous alignment result. According to the invention, through multi-modal fusion, geometric differences among modals, such as movement or resolution differences during scanning, can be eliminated, the accurate position of the cardiovascular system on the tissue structure is ensured, finally, a composite image of accurate registration of the cardiovascular system and the tissue structure is obtained, artifacts can be found out, and clinical diagnosis can be assisted.

This invention provides methods for evaluating tissue structure in damaged or healing tissue. [Solution] A method for evaluating the results of pressure measurements on an undamaged patient's skin, a) A step of obtaining a pressure measurement scan on the patient's skin, b) A step of generating a pressure measurement map, Methods that include...

The invention relates to the technical field of puncture path planning, in particular to a puncture path planning method for abdominal puncture drainage of severe acute pancreatitis. Firstly, a CT image and an MRI image are fused to construct an abdominal cavity three-dimensional model, tissue areas (an organ area, a blood vessel area and a focus area) are obtained through segmentation, and candidate paths are generated based on a target position and a preset body surface approach point; then, calculating a risk coefficient based on geometric features (including an included angle, a length and proximity to a tissue region) of the candidate path, and screening a preliminary optimal path; determining a puncture body position and a gravity component direction by combining a sagittal plane / coronal plane position relationship, analyzing tissue density distribution, and quantifying a tissue deformation interference index; finally, the risk coefficient and the deformation index are fused, re-screening of the paths is achieved, the optimal and alternative paths are determined, and therefore key tissue structures can be effectively avoided, the intraoperative displacement risk is reduced, and puncture accuracy and stability are improved.

Disclosed herein is an implantable or wearable, flexible, miniaturized microimaging suited for localized brain fluorescent imaging. The microimaging device is implemented on a Parylene photonics platform, which is biocompatible and fabricated using scalable planar microfabrication techniques, enabling customizable design, size, and number of channels (pixels). Operating across the entire visible spectrum. The microimaging device functions effectively both for coherent and scattered light. The microimaging device can be implanted into the brain of freely moving animals, where one or more waveguides could be dedicated to light delivery and the rest of the waveguides for collecting and relaying the fluorescent image to image the tissue structure and function.

This disclosure provides a method for identifying and counting unlabeled (native) blood cells and analytes in whole blood. In particular, this disclosure relates to devices used within the body equipped with microfluidic cytometry optical sensors and detectors that recognize analytes or histological architecture from within a patient to provide clinically actionable data related to the subject's health.