63 results about "Parenchyma" patented technology

The invention discloses an active / inactive pulmonary tuberculosis recognition system based on an improved 3D network, and the system comprises an image feature obtaining module which is used for obtaining pulmonary tuberculosis CT chest image features; the data preprocessing module is used for carrying out data preprocessing on the obtained pulmonary tuberculosis CT chest image features; the image segmentation module is used for segmenting the preprocessed pulmonary tuberculosis CT chest image features to obtain pulmonary parenchyma image features, and an adopted segmentation model is a 3D ResUNet segmentation model; the image classification and recognition module is used for performing prediction and classification on the lung parenchyma image features after image segmentation; wherein the adopted image classification model is a 3D ResUNet50 classification model, and the 3D ResUNet50 classification model is combined with a multi-scale attention module to obtain image output features; then, image output features are processed by adopting grouping convolution and channel shuffling, the types of active and inactive pulmonary tuberculosis are predicted, and confidence scores of the model are generated; the CT image classification accuracy of the model can be improved.

Modular mucosal tissue bioreactors combined with bioartificial mucus provide a high-fidelity, medium-throughput platform for evaluating CF treatments and modeling host-pathogen biology, a stepping stone towards better options for HEMT-nonresponsive patients. Whole lung ex vivo Cystic Fibrosis model system allows for investigation of candidate CF therapies.

The invention relates to the technical field of medical informatics, and provides an interstitial lung disease HRCT image analysis method and system based on artificial intelligence. The method comprises the following steps: performing pulmonary parenchyma segmentation processing on an input HRCT image to obtain a pulmonary parenchyma region; performing multi-category lesion segmentation on the pulmonary parenchyma region to obtain a segmentation mask; performing quantitative calculation on lesion distribution characteristics according to the segmentation mask to obtain lesion distribution parameters; and carrying out image mode classification according to the segmentation mask and the lesion distribution parameters to obtain a classification result. According to the method, the efficiency and precision of HRCT image analysis are improved, and the application range of HRCT image analysis is expanded.

The invention provides a kidney ultrasonic image analysis system and method, and the method comprises the steps: extracting the structural features of a kidney parenchyma region from a collected B-mode ultrasonic image sequence, and extracting the blood flow features of a corresponding region from a collected color Doppler blood flow image sequence; determining a blood flow distribution index diagram reflecting kidney blood flow distribution according to the blood flow characteristics, and then performing regional adaptive enhancement on the B-mode ultrasonic image sequence through the blood flow distribution index diagram to generate a B-mode reference image with an enhanced signal-to-noise ratio and a prominent skin medullary boundary; and fusing the B-mode reference image with a peak blood flow distribution diagram generated from the blood flow image sequence to obtain a fusion enhanced image when kidney skin marrow segmentation is performed on the kidney of the target patient. By adopting the scheme of the invention, pixel-level fusion can be carried out on the B-mode ultrasonic image and the color Doppler blood flow image based on the blood flow distribution in the color Doppler blood flow image.

The present application relates to the technical field of lung image marking auxiliary reading, in particular to an auxiliary reading system suitable for lung cryptococcosis patients. The present application firstly acquires continuous CT slice images of the lung, and extracts the foreground connected domain of the lung parenchyma region as the connected domain to be analyzed; further, according to the monotonicity of the width change of the target connected domain, the blood vessel possibility of the target connected domain is acquired; further, according to the monotonicity of the area change of the connected domain to be analyzed at the same position, the possibility of the target connected domain penetrating through the blood vessel is acquired; the degree of the target connected domain being similar to a circle is acquired; finally, according to the degree of being similar to a circle, the blood vessel possibility and the possibility of penetrating through the blood vessel are fused, and the target connected domain is marked. The present application measures the possibility of the target connected domain belonging to the blood vessel from the width change and the area change, and fuses the blood vessel possibility and the possibility of penetrating through the blood vessel by means of the degree of being similar to a circle, so as to accurately mark the connected domain and assist the relevant personnel in reading.

This document describes devices for in vivo drug testing in the brain. This document also describes implantable devices for long-term drug delivery to the brain parenchyma, and for access to biomarkers from the parenchyma.

The invention relates to a method and a device for automatically identifying benign and malignant kidney cystic lesions based on magnetic resonance images. The method comprises the following steps: S1, preprocessing and standardizing a T2 weighted image, a diffusion weighted image, an apparent diffusion coefficient image, a T1 weighted image, a skin medullary phase image, a parenchyma phase image and an excretion phase image; s2, respectively training automatic segmentation models corresponding to different images in a targeted manner, and predicting a focus by using the automatic segmentation models; s3, extracting morphological features, first-order features and textural features of the lesions from all the lesions, wherein the morphological features, the first-order features and the textural features comprise features of capsule walls, partitions and nodules of the lesions; screening the extracted features, and constructing a classification model by using the features with good robustness; and S4, preprocessing and standardizing the image of the current patient, respectively inputting the image into each corresponding automatic segmentation model, and operating the segmentation model and the classification model to realize benign and malignant recognition based on image recognition. According to the invention, integrated and automatic benign and malignant accurate diagnosis of kidney cystic lesions is realized.

The present application relates to a kind of implantable fixation device and method for mouse spinal cord administration, the device includes: catheter assembly, which includes sleeve, injection inner tube and locking nut, the catheter assembly is used to carry out fixed-point infusion in spinal cord parenchyma by the bone hole opened on vertebral vertebra;Vertebra fixation assembly, which includes two V-shaped supports for clamping and fixing on the two sides of the outer periphery of vertebra;And bonding reinforcement system, which includes the initial solid seal layer formed by adhesive to realize the sealing between bone hole and catheter assembly and the structural holding adhesive resin layer formed by resin to realize the fixation between vertebra fixation subassembly and vertebra.The present application designs special vertebra fixation assembly: V-shaped support, and is combined with "biological glue preliminary adhesion" and "dental cement overall wrapping", and constructs a multi-level, rigid-flexible combined "sandwich fixation" composite fixation system.

Bioadhesive and biodegradable polymeric nanoparticles can be administered intrathecally, for example, via the cisterna magna, into the spinal column to allow widespread distribution for the treatment of tumors such as leptomeningeal metastases. The nanoparticles rapidly spread to all cerebrospinal fluid (CSF) compartments, including the brain parenchyma and spinal column. The bioadhesive nanoparticles penetrate and are retained for long periods of time, during which time they can continue to release drugs. These nanoparticles can be loaded with different therapeutic, preventive, or diagnostic agents, most preferably DNA repair inhibitors, to enhance the killing of leptomeningeal tumors, such as leptomeningeal metastases, and disseminated tumors, such as medulloblastoma. In a preferred embodiment, patients are treated with a combination of a PARP inhibitor and temozolomide.

The invention provides a pepper pungency degree rapid detection method based on specific parenchyma cell thickness and application, and belongs to the technical field of pepper quality detection. According to the method, the pungency degree can be rapidly calculated by taking the radial thickness of the specific parenchymal cells on the inner side of the peel of the fresh red chili fruit as a morphological marker, measuring the thickness through sampling, vibration slicing and microscopic observation and substituting the thickness into a linear regression equation y = 25.751 x-3078.4, x is the cell thickness [mu] m, and y is a predicted Scovier index SHU. According to the method, the direct correlation between the pungency degree of the pepper and the cell morphology parameters is established for the first time, and the limitations of high cost, long period and sample damage of a traditional high performance liquid chromatography method are broken through, and the bottleneck of poor model universality of a near-infrared analysis method is broken through. The method has the outstanding advantages of being non-destructive, high in efficiency, low in cost, high in precision and the like, is particularly suitable for large-scale rapid screening of processing type pepper breeding populations, and remarkably accelerates the breeding process.

This invention relates to the field of medical image processing technology, specifically to an automatic detection and classification method and system for intracranial hemorrhage based on three-window CT fusion and label-dependent graph neural network, including the following steps: S100, acquiring the original CT slice image of the head to be detected, performing grayscale mapping on the original slice image based on preset brain window, subdural window and bone window respectively, and stacking the three mapped images along the channel dimension to generate a three-channel fused image; This invention greatly enriches the model's global perception ability of multi-level physiological structures such as brain parenchyma, microhematomas and skull lesions through innovative three-window physical mapping and channel fusion; it introduces a hybrid adjacency matrix graph neural network that combines prior knowledge of neuroradiology with data-driven approach, explicitly establishing pathophysiological causal relationships between various hemorrhage subtypes at the model architecture level, effectively eliminating logical contradictions in predictions that violate clinical common sense.

The invention provides a bamboo fiber bundle and parenchyma tissue separation method, and belongs to the technical field of bamboo wood processing. The method comprises the steps that firstly, bamboo blocks are soaked to be in a saturated state, bamboo slices with the thickness of 45-90 microns are cut out along textures, and the bamboo slices are kept wet; then, the wet sheet is tightly attached to a smooth plane and dried at the normal pressure of 80-120 DEG C or the vacuum temperature of 45-70 DEG C, and cracks capable of being used for separation are generated along the texture of the sheet through constraint shrinkage stress; physically stripping the fiber bundle from the thin-walled structure along the crack; finally, respectively wetting, fixing and slowly drying the fiber bundle sheets and the thin-walled tissue sheets to prepare complete fiber bundle sheets and thin-walled tissue sheets; according to the method, the interface directional cracking is induced through controlled drying, efficient and low-damage separation of the bamboo fiber bundles and the parenchyma tissue is achieved, and the problems that in the prior art, long fiber bundles and large-area parenchyma tissue slices cannot be obtained at the same time, the process is complex, and pollution is large are solved. The method is easy and convenient to operate, environmentally friendly and feasible, and the obtained product is high in integrity and suitable for the fields of spinning, composite materials, micromechanics research and the like.

The invention discloses a pharmaceutical composition for improving or treating ovarian cancer as well as a preparation method and application of the pharmaceutical composition. The invention provides an engineered cell and a new method capable of remarkably enhancing the migration and infiltration capacity of immune cells to an ovarian cancer parenchyma part and relieving tumor immune escape, so that the defect that the immune cells are difficult to effectively infiltrate to the ovarian cancer parenchyma in the prior art is overcome, and the curative effect of ovarian cancer immunotherapy is remarkably improved.

Described is a method of repairing the parenchyma of the brain. The method comprises implanting a biodegradable porous polymeric matrix block, such as a piece of collagen matrix, to a void in the brain through a tubular device. A medical device for use in the method is also described.

The present disclosure is directed towards devices, methods, and related systems that are minutely-invasively delivered to the brain parenchyma, subdural or subarachnoid space where the devices, methods, and systems directly interface with central nervous system media (i.e., fluid or tissue) enabling detecting, sensing, measuring, stimulating, altering and / or modulating of the media or tissue surfaces.

The invention discloses a Renal scoring method and device for kidney tumors, and belongs to the field of medical image processing. The method comprises the steps that segmentation data are acquired, and the segmentation data comprise data of kidneys, tumors and blood vessels; anatomical analysis is carried out based on the segmentation data, the kidney principal axis, the renal pelvis position and the ureter are determined, and a natural coordinate system of the kidney is established; calculating the maximum diameter of the tumor based on the tumor voxel, and determining an R score according to the maximum diameter of the tumor; constructing a kidney convex hull based on the kidney parenchyma coordinates, and determining an E score based on the proportion of tumor voxels inside and outside the kidney convex hull; taking the ureter as a set system, determining the minimum distance from the tumor voxel to the set system, and determining an N score according to the minimum distance; constructing a natural interface based on the pelvis position, and determining an A score based on the natural interface; detecting polar lines based on the renal door depression, and determining an L score according to the polar lines. The method provided by the invention eliminates the subjective judgment difference of the scorer.

This invention belongs to the field of medical image processing technology, specifically relating to a kidney segmentation method based on key point localization. The method includes the following steps: acquiring medical images of the kidney to be segmented and preprocessing the images; defining a set of anatomical key points specifically for kidney segmentation; predicting the position coordinates of each key point in the key point set using a model; constructing spatial topological relationships between key points based on the predicted key point coordinates and kidney anatomical zoning rules; and dividing the kidney parenchyma into regions according to the spatial topological relationships and kidney anatomical zoning rules, outputting the segmentation results for each kidney segment. This invention achieves efficient and accurate automatic kidney segmentation by precisely detecting anatomical key points and combining them with the anatomical rules of the Graves kidney segment model, outputting segmentation results with anatomical interpretability, and providing reliable technical support for preoperative planning of urological surgeries such as precise nephrectomy.

The present application belongs to the technical field of dehydrating agent, and particularly relates to a dehydration reagent for biological tissue as well as a preparation method and application thereof. The dehydration reagent comprises a dehydrating agent and an infiltrating agent. The dehydrating agent comprises ethanol, and the infiltrating agent comprises glycerol. Through the synergistic dehydration effect of the ethanol-glycerol mixed solution, the short board of lipid loss caused by single ethanol dehydration is made up. The lipid structure such as cell membrane and cell organ membrane is effectively protected in the dehydration process and is no longer excessively extracted, so that the full form of the cell is maintained, and the volume of the whole brain parenchyma remains stable after dehydration, effectively reducing the volume shrinkage of the biological tissue and maintaining the morphological stability.

The invention discloses a stone cell high-purity separation method suitable for a pear fruit development stage, which comprises the following steps: selecting fruit pulp tissues of young pear fruits 30 days after a full-bloom stage, performing freezing grinding treatment, and performing low-temperature pretreatment by using 0.5 mM HCl to destroy pectin connection and weaken intercellular adhesive force; then adding pectinase, carrying out selective enzymolysis under a mild condition, and removing parenchyma cell residues attached to the surfaces of the stone cells; washing with 70% ethanol and acetone to remove cell membranes and pigment components so as to improve the purity of the sample; and finally, enriching the high-density stone cell population by utilizing a Percoll density gradient centrifugation technology to obtain the high-purity stone cells which are complete in structure and free of obvious impurities. The method is easy and convenient to operate and high in repeatability, is particularly suitable for research of the lignification starting and expansion stage of the stone cells in the early development stage, provides a new platform for functional research of the high-lignification structural cells of the plants, and has important scientific research value and application and popularization prospects.

A system for detecting an air leak in the lung parenchyma and / or airway may have a heater configured to vaporize at least one fluid into an aerosol. A conduit system may include a conduit portion configured to be received in a user's airway. A motive flow source is connected to the conduit system for inducing a flow of the aerosol into the conduit portion. A controller is configured for operating the heater to generate the aerosol, and for controlling the motive flow source to induce the flow of the aerosol into the conduit portion at a flow rate of a given level. A method for detecting an air leak in the lung parenchyma and / or airway is also provided.

The present disclosure discusses a devices, systems and methods for transvascular, transvenous and / or transdural access, to the brain parenchyma, subarachnoid or subdural spaces. In some embodiments, the disclosed systems and methods may be used for local drug delivery, tissue biopsy, nanofluidic or microelectronic device / component delivery / insertion / implantation, in situ imaging, ablation of abnormal brain tissue and the like. Embodiments of the present disclosure include an access catheter system for extravascular procedures in the brain having an elongate, flexible tubular body, with at least one lumen extending axially there through between a proximal end, and a distal end. The access catheter system may include a side exit port and a distal end port. Further, the access catheter system may include a selective deflector positioned within the lumen configured to deflect a procedure catheter and permit a guide catheter.

The application relates to the field of intelligent medical treatment, in particular to a thyroid ultrasound image data enhancement method, device and program product. The method comprises the following steps: acquiring a thyroid ultrasound image; segmenting the thyroid ultrasound image to obtain a fascia mask and an adenoid parenchyma mask; calculating the distance from each pixel to the nearest edge pixel of the fascia mask to generate a distance map, and calculating the weight of each pixel through the distance map to generate an anatomical weight atlas; performing smoothing processing on the thyroid ultrasound image through the anatomical weight atlas to obtain an illumination layer; removing the pixel component of the illumination layer on the pixel of the thyroid ultrasound image to obtain a texture layer; performing directional filtering on the texture layer to obtain a direction selection coefficient; performing gate control on the tissue region of the adenoid parenchyma mask to obtain a tissue gate map; enhancing the texture layer through the direction selection coefficient and the tissue gate map to obtain an enhanced texture layer; and combining the illumination layer and the enhanced texture layer to obtain an enhanced image. The application has good clinical value.

The application discloses a pneumoconiosis staging recognition method and system based on multi-modal artificial imaging feature fusion, and relates to the technical field of medical image recognition. The method comprises the following steps: standardizing and pre-processing an input chest X-ray image and extracting a lung field region; in the lung field region, detecting and counting micro nodules based on clinical imaging prior knowledge, and extracting micro nodule quantity features reflecting the quantity and spatial distribution characteristics of nodular lesions; calculating the first-order entropy features of the lung field region image to quantify the complexity of lung parenchyma texture, and extracting high-dimensional features representing gray heterogeneity and structure statistical characteristics by using an imaging feature analysis method. The multi-class artificial imaging features are standardized and fused in a unified feature space, and the fused features are input into a learning classification model for pneumoconiosis period recognition. The application improves the stability and interpretability of pneumoconiosis staging recognition through multi-modal artificial imaging feature fusion modeling.

The invention provides a construction method and application of a cerebral venous sinus thrombosis animal model. Comprising the following steps: injecting a photosensitizer into superior sagittal sinus of an experimental animal; the upper sagittal sinus is irradiated with a laser to induce photochemical thrombosis. According to the construction method of the CVST animal model, the modeling time can be shortened, meanwhile, thrombus can be accurately and stably formed in the superior sagittal sinus, venous infarction is completely simulated, and iatrogenic brain parenchyma injury and thrombus formation of unexpected parts are avoided. The animal model prepared by the invention can be used for researching CVST-related pathophysiological mechanisms, intervention thereof and the like, and is stable and wide in application.

The invention provides a lung image recognition method and system for clinical diagnosis of the respiratory medicine department. The method comprises the steps that a binary mask containing complete lung parenchyma is obtained from a lung image; segmenting a target lung field image from the lung image based on the binary mask, and extracting a texture saliency map from the target lung field image; performing pixel-level fusion on the texture saliency map and the target lung field image to obtain a lung feature image, and performing multi-resolution pyramid decomposition on the lung feature image to obtain a Gaussian pyramid layer and a Laplacian pyramid layer; direction gradient histogram features and local binary pattern features are extracted from the Gaussian pyramid layer and the Laplacian pyramid layer respectively, and then a multi-resolution joint feature vector is constructed; and inputting the multi-resolution joint feature vector into a pre-trained image analysis network, and positioning a focus area in the lung image. According to the technical scheme provided by the invention, the lesion area in the lung image can be identified under the coupling interference of the anatomical structure and the pathological features.

The application provides a lung recognition processing method and device and a server, relates to model processing technology, and the method comprises the following steps: obtaining a model recognition instruction, the model recognition instruction comprises a lung model identifier, determining a lung model corresponding to the lung model identifier, and the lung model comprises a lung parenchyma model, a trachea model, a pulmonary vein model and a pulmonary artery model. Based on the growth information of at least one of the trachea model, the pulmonary vein model and the pulmonary artery model, a plurality of initial segmentation cross sections of the lung parenchyma model are determined. According to at least one of the intrasegment trachea, intrasegment vein and intrasegment artery in each initial lung segment, a plurality of target segmentation cross sections of the lung parenchyma model are generated. According to the target segmentation cross sections of the reconstructed lung model, the distribution information of each lung segment can be obtained, thereby helping to improve the accuracy of the surgical plan, reduce the surgical risk index, improve the surgical success rate, and solve the technical problem that it is difficult to recognize the distribution of the intrapulmonary trachea, blood vessels and lung segments.

This invention relates to an animal model of mediastinal lymph node metastasis in lung cancer and its construction method. The core of this invention lies in the precise intrapulmonary in situ microinjection technique to directly implant human lung cancer cells into the lung parenchyma of immunodeficient mice. Utilizing the natural lymphatic drainage pathway of the lung tissue, tumor cells are induced to migrate to the mediastinal lymph nodes, thus successfully constructing a complete metastasis chain model from the primary tumor to regional lymph nodes. This model can more realistically simulate the microenvironment and process of lung cancer lymph node metastasis, and is suitable for metastasis mechanism research, drug evaluation, and the development of personalized treatment strategies, possessing high translational medicine value.

The invention discloses an in-vitro implantation simulation platform, and the platform comprises a brain model which is provided with an inner cavity, and the wall surface of the brain model is provided with an implantation port, a communication inlet, and a communication outlet which are communicated with the inner cavity; the shaping piece is detachably arranged in the inner cavity; according to the in-vitro implantation simulation platform, when the inner cavity is filled with the brain parenchyma simulant, the shaping piece is installed between the communicating inlet and the communicating outlet, after filling is completed, the shaping piece is detachable so that a hollow channel can be formed in the brain parenchyma simulant, and the hollow channel communicates with the communicating inlet and the communicating outlet and is used for allowing the cerebrospinal fluid simulant to flow through. According to the in-vitro implantation simulation platform provided by the embodiment of the invention, the mechanical properties of the brain tissue and the flow of the cerebrospinal fluid are integrated into the in-vitro model, the influence of the flow of the brain tissue and the flow of the cerebrospinal fluid on the implant can be simulated at the same time, the repeatability is high, and a standardized simulation platform is provided for mechanical property evaluation and optimization design of the brain implant. And the requirements of animal experiments can be reduced.

The application discloses an activity / inactivity tuberculosis recognition system based on an improved 3D network, which comprises an image feature acquisition module, a data preprocessing module, an image segmentation module and an image classification recognition module. The image feature acquisition module is used for acquiring lung tuberculosis CT chest image features. The data preprocessing module is used for performing data preprocessing on the acquired lung tuberculosis CT chest image features. The image segmentation module is used for segmenting the preprocessed lung tuberculosis CT chest image features to acquire lung parenchyma image features, and a segmentation model adopted is a 3D ResUNet segmentation model. The image classification recognition module is used for performing prediction classification on the lung parenchyma image features after image segmentation. An image classification model adopted is a 3D ResUNet50 classification model, and the 3D ResUNet50 classification model is combined with a multi-scale attention module to obtain image output features. Then, grouping convolution and channel shuffling are used to process the image output features, the categories of active and inactive tuberculosis are predicted, and the confidence score of the model is generated. The application can improve the CT image classification accuracy of the model.