44 results about "Renal stone" patented technology

The invention belongs to the technical field of deep learning, and particularly relates to a kidney and kidney stone segmentation method for a computed tomography image and electronic equipment. Comprising the following steps: S1, carrying out data preprocessing and data enhancement on a CT image data set; s2, constructing a semantic segmentation model for segmenting the CT image; s3, constructing a composite loss function fusing a cross entropy loss function and a loss function based on a Dice coefficient for training the semantic segmentation model; s4, setting a learning rate change curve, performing 2D slicing on the CT image data, and training a semantic segmentation model by using the 2D slices; and S5, segmenting the kidney and the kidney stone in the CT image by using the trained semantic segmentation model. According to the method, data preprocessing and data enhancement are performed by combining data set statistical parameters, Attention-gate and residual structures are introduced to construct the segmentation model, and finally, a proper training and prediction strategy is adopted, so that the segmentation accuracy of the kidney and the kidney stone in the CT image is improved.

An endoscope includes a handle including a handle housing, an irrigation inlet port adapted to receive irrigation fluid, and an irrigation channel; and an insertion cord extending distally from the handle. The insertion cord includes an insertion tube; a bending section extending from the insertion tube; a distal tip extending from the bending section and including a tip housing; a camera at least partially enclosed in the tip housing; interstitial space within the insertion tube in fluid communication with the irrigation channel; and at least one interstitial flow opening in fluid communication with the interstitial space and adapted to discharge the irrigation fluid.

This invention relates to the field of medical biopolymer materials technology, specifically to an injectable hydrogel for kidney stone removal, its preparation method, and its application. The preparation materials include at least a precursor solution 1 and a precursor solution 2. Precursor solution 1 contains at least a polyethylene glycol derivative and a thickener, while precursor solution 2 contains at least a polyamino polymer. By optimizing the formulation ratio of the two-component precursor solutions, a hydrogel with strong conformability, good toughness, and viscosity is formed in situ in the kidney stone area. This encapsulates the kidney stone, facilitating its removal from the body and avoiding the safety hazards associated with small kidney stone fragments or conventional drug treatment.

This invention discloses a method and system for predicting kidney stone hardness based on cross-modal aligned knowledge distillation, comprising: training a teacher network using multi-channel DECT data, enabling the teacher network to predict stone hardness and extract the physical attribute vector Φ. DECT ;Φ DECT The dimension is d p Each dimension corresponds to a physical attribute that plays a decisive role in hardness prediction; a student network is constructed, which, after receiving a single-channel SECT image, first generates a latent physical attribute vector and then performs hardness prediction based on the latent physical attribute vector; an alignment loss is constructed, which, during the training of the student model, allows the distribution and geometry of to approximate Φ. DECT The SECT image to be predicted is input into the trained student model to predict the hardness of the kidney stone. This invention can transfer rich information from dual-energy CT to a plain CT model to improve the predictive ability of plain CT for kidney stone hardness.

The application relates to the technical field of kidney stone operation management, and discloses a multi-dimensional management system based on clinical data of kidney stone operation. A preoperative data integration module of the system receives and integrates image data from CT, ultrasound, X-ray and other devices, and generates a three-dimensional stone distribution model through spatial registration. A surgical risk assessment module extracts parameters such as stone volume, density and position based on the model, combines physiological indicators and historical operation data of the patient, and calculates a surgical difficulty coefficient and a complication probability. An intraoperative real-time monitoring module collects endoscope video, laser parameter and flushing liquid pressure data, and updates the stone crushing state and residual volume in real time. A tissue damage early warning module analyzes the laser energy distribution and the tissue contact time, assesses the thermal damage risk and generates a safe operation boundary. A postoperative recovery prediction module integrates the operation data and the metabolic characteristics of the patient, and predicts the stone clearance rate and the recovery progress of the kidney function.

A method of using a suction device to remove an object from a subject's body includes extending a suction device into the body through a lumen of a medical device and expanding the suction head from a contracted configuration to an expanded configuration within the body. The suction head may be provided at a distal end of an elongate conduit. The method may also include applying suction to move the object into the expanded suction head, and removing the suction device with the object from the body.

The invention discloses a kidney stone, hydronephrosis and pyosis detection system based on multi-scale feature fusion, and belongs to the technical field of medical detection, and the working process of the detection system comprises the following steps: S1, image data acquisition and preprocessing; s2, feature extraction and multi-scale feature fusion of the model; s3, classification decision and output layer design; and S4, model training and optimization. According to the system, from original DICOM image input to final diagnosis report generation, full-process automatic processing is achieved, manual intervention on feature engineering or intermediate steps is not needed, the system can generate a structured diagnosis report which comprises specific disease classification, confidence score and visual evidence heat map, the output format is normative, and the diagnosis report can be used for diagnosis. The method is easy to integrate with an existing image archiving and communication system of a hospital, and the model is clearly guided to pay attention to specific features related to ponding and infection in the learning process by introducing independent ponding and infection auxiliary discrimination branches and performing joint optimization with a main classification task.

The application belongs to the field of biomedicine, and particularly relates to application of CRYL1 protein in preparation of products for evaluating, diagnosing or assisting in diagnosing postoperative recurrence risk of calcium oxalate kidney stone combined with renal papillary calcium plaque, and a sequence of the CRYL1 protein is shown as SEQ ID NO. 1. The application firstly finds that expression of CRYL1 protein in renal tubular and collecting duct cells of renal papillary calcium plaque tissue is reduced, and it is proved through experiments that urine CRYL1 protein is a postoperative recurrence predictor and prediction marker of patients with CaOx kidney stone combined with renal papillary calcium plaque, and a CRYL1 protein detection kit is further developed for detecting or evaluating postoperative recurrence risk of patients with CaOx kidney stone combined with renal papillary calcium plaque, which promotes personalized follow-up and prevention scheme of the patients, and has great application prospect in the clinic.

The application relates to the technical field of medical image processing, in particular to a small kidney stone automatic segmentation and three-dimensional positioning method based on a CT image. The method determines local saliency according to the gray level difference between the inner layer analysis area and the outer layer background area of pixels and the gray level fluctuation degree of the outer layer, filters out candidate points, obtains the structure regularity of the candidate points according to the radial monotonicity and direction consistency of the gray level distribution in the candidate point window, divides a plurality of concentric annular zones with the candidate points as the center, calculates the annular zone gray levels of the annular zones, determines the scale matching degree according to the annular zone gray level variation trend and the relative concentration degree of the annular zone gray level difference, determines the comprehensive confidence degree according to the saliency, the regularity and the matching degree, adjusts the contrast parameter of the level set edge indication function according to the comprehensive confidence degree, drives the level set evolution by using the adjusted function, obtains the segmentation contour and the three-dimensional space positioning of the target, and thus the weak edge missing detection and the false positive rate of the target are reduced.

The application discloses a kidney stone load evaluation method and device based on CT plain scan images, and relates to the technical field of medical image processing. The method comprises the following steps: automatically analyzing and recording semantic coordinates of each lesion area, constructing a structured data set, and constructing a local feature space for the lesion. The semantic boundary of the suspected kidney stone in the CT plain scan image sequence is used to judge the lesion morphology by exploring the corresponding semantic features in the local feature space through a morphological method. A density space matrix is constructed by using the semantic features of the lesion, an optimal semantic density is calculated in the density space matrix by designing a search strategy corresponding to the lesion morphology, and the number of kidney stones is obtained by using an unsupervised clustering algorithm. According to the analysis results of the morphology and number of the kidney stones, the automatic volume measurement of the kidney stones is realized by using a graphics method. The application can realize the full-automatic and accurate measurement of the morphology, number and volume of the kidney stones in the CT plain scan image sequence.

The utility model belongs to the technical field of medical instruments, and particularly relates to a miniature lens line for treating kidney stone, which comprises a flexible circuit board, a miniature image sensor, LED (light-emitting diode) modules, a capacitor, a wire rod and an elastic sleeve, the miniature image sensor is arranged at the front end of the flexible circuit board and located between the two LED modules, the capacitor is arranged on the flexible circuit board, the wire rod is connected to the position, away from the front end of the flexible circuit board, of the flexible circuit board, and the elastic sleeve at least covers part of the wire rod and the connecting position of the wire rod and the flexible circuit board. Epoxy resin glue for packaging the joint of the wire rod and the flexible circuit board is injected into the elastic sleeve. When in use, the miniature lens wire enters the ureteroscope and is repeatedly bent by 250 degrees, so that a welding spot at the joint of the wire and the flexible circuit board cannot be broken, the bending service life is longer, and the use stability is more reliable.

This invention discloses an intelligent identification method for hepatobiliary and renal stones based on ultrasound images, belonging to the field of stone identification technology. The method includes the following steps: acquiring an ultrasound image to be detected and marking it as a real-time detection image; obtaining real-time detection grayscale values ​​based on the real-time detection image; obtaining organ grayscale thresholds based on ultrasound images in a database; obtaining real-time organ regions based on the real-time detection grayscale values ​​and organ grayscale thresholds; constructing real-time stone detection values ​​based on the real-time organ regions; obtaining historical normal boundary values ​​based on ultrasound images in a database; obtaining stone boundary thresholds based on the historical normal boundary values; and determining whether gallstones are present based on the real-time stone detection values ​​and stone boundary thresholds. This invention addresses the problem that existing stone identification technologies suffer from poor accuracy due to significant noise in ultrasound images.

This invention discloses a kidney stone risk prediction system based on big data, belonging to the field of risk prediction technology. Specifically, it includes: collecting electronic medical records, historical dietary questionnaires, and water quality mineral content data of the target area population; constructing a multidimensional heterogeneous dataset containing physiological and biochemical indicators, dietary structure characteristics, and environmental water quality factors; establishing a mapping relationship between dietary components and urine solute concentration; converting discrete dietary records into continuous time-series vectors and fusing them with water hardness coefficients; subsequently, mining lag response patterns through metabolic network association analysis to construct a metabolic response knowledge graph; simulating the solute precipitation process based on this graph, calculating dynamic supersaturation, and generating a crystallization saturation potential energy curve; finally, inputting the curve into a temporal convolutional neural network to extract features to predict the probability of kidney stone crystal aggregation within a specific future time window for an individual.

The utility model discloses kidney stone extraction net basket belongs to medical instrument technical field, and the lower fixedly connected with the finger hole ring has the net basket handle, the surface slidingly connected with the sliding block has the net basket handle, and the both sides symmetry of sliding block fixedly connected with handle ring, the upper portion of net basket handle is provided with sheath pipe, and the upper portion of sheath pipe is provided with net basket, the upper portion of sliding block one side is provided with limit component, and the upper portion of net basket is covered with protection component, the utility model sets up limit component, and when being convenient through the sliding block drive net basket basket and take the stone, can limit the fixed sliding block, thereby prevent falling, and through reset component, make sliding block can automatic reset, improve the practicality of use, the utility model sets up protection component, and after use, can carry out the protection to the end, and the positive pole magnetic stripe and negative pole magnetic stripe are convenient for installing the positioning of protection cover, improve the practicality of use.

The application discloses a method for removing residual pieces of kidney stones under fluorescence guidance, and belongs to the technical field of medical devices. The method first establishes a database containing standard fluorescence spectrum curves of different types of stones. During the operation, a multispectral imaging system integrated in an endoscope emits excitation light of at least three wavelengths and collects a time sequence of multispectral fluorescence images of the operation area. The background and target spectrum are separated by a spectral decomposition algorithm, and the target spectrum is matched and identified with the database to locate the residual pieces of stones. Finally, the identification result is superimposed in real time on the endoscope white light image as a highlighted signal to generate an augmented reality guide image, which guides the doctor to accurately remove the residual pieces of stones and finally confirms the removal through systematic scanning and data backtracking. The application solves the problem of low identification rate and high missed detection rate of small and hidden residual pieces of stones in traditional operations, realizes high-specificity identification and intuitive spatial guidance, and significantly improves the completeness of removal and the operation efficiency.

The invention provides rhamnogalacturonan I, a pharmaceutical composition as well as a preparation method and application of the rhamnogalacturonan I, and belongs to the field of biotechnology and chemistry. New rhamnogalacturonan-I is separated from polygonum aviculare, and the structure and performance of the rhamnogalacturonan-I are characterized. Experiments show that the novel rhamnogalacturonan I can play a role in resisting kidney stone. The novel rhamnogalacturonan I disclosed by the invention has important clinical significance and application prospects in preparation of medicines for preventing and / or treating kidney stones.

The present application relates to the technical field of medical diagnosis system, specifically to a kidney stone composition intelligent identification and individualized prevention and treatment scheme generation system, which comprises a stone type identification module, a composition correlation determination module, an acid-base state division module, a metabolic behavior ordering module and a path scheme construction module.In the present application, the linkage characteristics of the local structure and energy state of the stone surface are extracted through the corresponding relationship of the image texture and the spectral peak position in space, the continuous form of the composition change on the time axis is captured through the period comparison mode of the consistent trend direction, the structural change of the metabolic state in the stage is drawn through the collaborative control of the multiple biochemical trends of lactic acid and bicarbonate in the unified time scale, the mode track of the metabolic behavior is tracked through the difference of the behavior direction change frequency in the period, the path sequence of the metabolic correlation behavior is constructed through the step-by-step promotion of the trend relationship in the period, and the dynamic linkage recognition ability between the data and the stage adaptation ability of the individual intervention path are enhanced.

The present disclosure teaches the use of endoscopic surgical lasers with beam diffraction. During lithotripsy, an endoscope probe with a laser fiber is deployed. A diffraction grating within the optical core of the laser fiber disperses laser energy to a larger area for more effective ablation of kidney stone.

The invention relates to the technical field of kidney stone operation management, and discloses a multi-dimensional management system based on kidney stone operation clinical data. A preoperative data integration module of the system receives and integrates image data from CT equipment, ultrasonic equipment, X-ray equipment and the like, and a three-dimensional stone distribution model is generated through spatial registration. The operation risk assessment module extracts the size, density, position and other parameters of the calculus based on the model, and calculates an operation difficulty coefficient and a complication probability in combination with the physiological indexes of the patient and historical operation data. The intraoperative real-time monitoring module collects endoscope videos, laser parameters and flushing fluid pressure data and updates the stone breaking state and the residual volume in real time. The tissue damage early warning module analyzes laser energy distribution and tissue contact time, assesses thermal damage risks and generates a safe operation boundary. The postoperative recovery prediction module integrates the operation data and the metabolic characteristics of the patient, and predicts the calculus removal rate and the renal function recovery progress.

Devices, systems, and methods are provided for breaking a kidney stone(s) into smaller particles, fragments, and / or stone dust; and removing the same from a patient. The medical device may include a tube having a distal end, a proximal end, a port located proximal of the distal end, and a length of the tube extending between the proximal end and the distal end. A first portion of the tube may be proximal of the port and have a first cross-sectional area, while a second portion of the tube may be distal of the port and have a second cross-sectional area smaller than the first cross-sectional area. A first lumen may extend from the proximal end to the distal end of the tube. A second lumen may in communication with the port to fluidly connect the proximal end of the tube with the port.

The utility model discloses a kind of kidney stone filtering collectors, belong to medical equipment technical field, including processing box, the top of processing box is detachably connected with collection pipe, the inner wall of processing box is fixedly connected with filter plate, the top of filter plate is provided with flushing mechanism, the bottom of the side wall of processing box is fixedly connected with drainage pipe, filter plate is obliquely arranged, the side wall of processing box is provided with discharge port, discharge port is located in the lower side of filter plate, discharge port is provided with plugging assembly, the lower side of filter plate is provided with knocking mechanism, the side wall of processing box is fixedly connected with support frame, support frame is placed with collection box above, discharge port is located above collection box.Autumn beneficial effect is in that: after washing after filtering stone by flushing mechanism, open discharge port, knock filter plate by knocking mechanism, make the stone on filter plate fall into collection box through discharge port, to facilitate the collection after filtering stone.

An endoscope includes a handle including a handle housing, an irrigation inlet port adapted to receive irrigation fluid, and an irrigation channel; and an insertion cord extending distally from the handle. The insertion cord includes an insertion tube; a bending section extending from the insertion tube; a distal tip extending from the bending section and including a tip housing; a camera at least partially enclosed in the tip housing; interstitial space within the insertion tube in fluid communication with the irrigation channel; and at least one interstitial flow opening in fluid communication with the interstitial space and adapted to discharge the irrigation fluid.

This invention has discovered that the pathogenesis of kidney stones is accompanied by a significant increase in the lactation modification level of histidine at position 147 of ALDOB. Furthermore, when histidine at position 147 is mutated, the lactation modification at position 147 of the mutant amino acid disappears. In vivo experiments show that this mutation can significantly inhibit the accumulation of calcium oxalate crystals in mouse kidneys, preventing the occurrence of kidney stones. Based on this, this invention provides a novel agent and pathway for the prevention and treatment of kidney stones.

The invention discloses a multi-task joint segmentation method for kidney stone and vascular calcification in a coronary CTA image, and relates to the technical field of image segmentation processing, and the segmentation method comprises the following steps: obtaining coronary CTA image data, constructing a multi-task joint segmentation network, inputting the standardized image data into a shared feature encoder, and obtaining a shared feature encoder; and performing inter-task feature interaction enhancement on the multi-scale feature representation through a task interaction module to obtain enhanced feature representation, respectively inputting the enhanced feature representation into a kidney stone segmentation decoder and a vascular calcification segmentation decoder, and generating a final joint segmentation mask image according to a kidney stone segmentation result and a vascular calcification segmentation result. The method has the advantages that the segmentation of kidney stone and vascular calcification is completed in a single network at the same time through a multi-task joint learning framework, and compared with a scheme of independently training two models, the model complexity and computing resource consumption are reduced, and the feasibility of practical application is improved.

The invention discloses a non-enhanced CT kidney stone automatic detection method based on multi-scale feature fusion, and relates to the technical field of clinical image diagnos.The method includes the steps that non-enhanced CT coronal position kidney image data are collected, de-identification processing is conducted on the collected non-enhanced CT coronal position kidney image data, and the non-enhanced CT coronal position kidney image data are obtained; processing the de-identified non-enhanced CT coronary position kidney image data through a data standardization and image enhancement method, extracting key image features by adopting a convolutional neural network, and establishing a kidney stone automatic detection model based on the extracted key image features; and finally, the final automatic kidney stone detection model is deployed to a high-performance workstation with GPU (Graphic Processing Unit) acceleration capability or is integrated with the existing PACS (Picture Archiving and Communication System) of a medical institution, so that a clinical automatic detection function is realized, automatic and efficient detection of kidney stones is realized, and the detection efficiency is improved. And powerful technical support is provided for clinical diagnosis.

The application discloses an artificial intelligence-based kidney stone extracorporeal lithotripsy detection system and method, and belongs to the technical field of kidney stone extracorporeal lithotripsy detection. In order to improve the detection accuracy of the ultrasonic image of the kidney stone extracorporeal lithotripsy, the application comprises the following steps: obtaining the B-ultrasonic image of the kidney of a patient with kidney stones, performing data processing, adopting an HRNe model to combine mean filtering and Sobel operator processing technology to construct a kidney stone recognition model of the ultrasonic image, evaluating the trained kidney stone recognition model of the ultrasonic image by using a verification set, calculating the accuracy, sensitivity and specificity, evaluating the accuracy and reliability of the trained kidney stone recognition model of the ultrasonic image in the kidney stone recognition task, further optimizing the trained kidney stone recognition model of the ultrasonic image, obtaining the stone features output by the optimized kidney stone recognition model of the ultrasonic image, calculating the kidney stone extracorporeal lithotripsy energy, and planning a kidney stone extracorporeal lithotripsy scheme. The application provides a more accurate scheme.

This invention relates to the field of medical device technology, and in particular to an integrated device for lithotripsy and stone removal of kidney stones with adjustable aperture, comprising an integrated tube; the integrated tube further comprises a lithotripsy module and a lithotripsy extraction module, and the other end of the lithotripsy module and the lithotripsy extraction module are connected to a pressure regulating module, which is used to adjust the air pressure in the internal pipes of the lithotripsy module and the lithotripsy extraction module respectively; during the lithotripsy and stone removal process, there is no need to repeatedly change the device, which can reduce damage to the patient and improve the efficiency of lithotripsy and stone removal. A flexible connector is provided between the laser lithotripsy probe and the connecting tube, and a first flexible air tube is arranged on its outer side; by injecting air into the first flexible air tube at different positions through the external pressure regulating module, air pressure difference is formed in each air tube, driving the controllable cover to bend, thereby driving the laser lithotripsy probe to deflect, realizing the adjustable probe angle, which facilitates precise fragmentation of stones at different positions and ensures the quality of lithotripsy.

This invention discloses a multifunctional percutaneous nephrostomy kit, relating to the field of kidney stone surgery. It includes an outer sheath with a hollow working channel inside, and a flexible endoscope sheath inserted into the working channel of the outer sheath. The bottom of the flexible endoscope sheath has a curved section. This invention inserts the flexible endoscope sheath into the outer sheath and then inserts a flexible endoscope into the flexible endoscope sheath. The bend on the flexible endoscope can drive the curved section on the flexible endoscope sheath to bend, placing the curved section in a bent state. By rotating the bend on the flexible endoscope, the orientation of the curved section can be changed, allowing for the extraction of stones at the insertion point of the outer sheath and in the area surrounding and above the insertion point, effectively improving the stone removal effect. Simultaneously, a fixing mechanism is provided to clamp the outer sheath with multiple clamping plates, eliminating the need for medical personnel to hold it by hand and ensuring the accuracy of subsequent operations.

The application relates to a kidney stone composition analysis method and system based on a B-ultrasound image. The kidney stone composition analysis system based on the B-ultrasound image comprises the following steps: constructing a deep learning model; acquiring a B-ultrasound image and preprocessing the B-ultrasound image; performing feature extraction on the preprocessed B-ultrasound image based on the deep learning model to obtain image features; performing feature processing on the image features to obtain processed image features; the feature processing comprises: performing weighted processing on the image features based on an attention mechanism and performing feature fusion processing on the image features and clinical information of a patient based on a dynamic feature fusion mechanism; the processed image features comprise weighted image features with attention weights and fusion image features; constructing a composition analysis model; inputting the processed image features into the composition analysis model for analysis to obtain kidney stone composition of the B-ultrasound image. The application can accurately and efficiently analyze kidney stone composition in a B-ultrasound image.

The invention belongs to the field of target detection, and discloses a kidney stone image target detection method and system based on an MSCA-RTDETR model, an improved feature pyramid network of CAFPN is introduced for an improved neck structure of an RT-DETR model, and the improved feature pyramid network comprises DMSF, MSFF and PCE modules to further improve multi-scale feature fusion and context information perception of the model. And the CAFE module is used for improving the understanding of the model on the context by integrating feature information of different levels. The MSFF module and the DMSF module realize multi-level feature fusion and improve the performance of multi-scale small-target kidney stone medical CT image target detection by means of dynamic interpolation and multi-scale feature integration. The PolaAttention EncodeLayer module can enhance modeling of the global context of the model and emphasize feature interaction, and the robustness of the model to sparse data is improved.