67 results about "Renal stone" patented technology

Kidney stone removal system is disclosed having components including a handle mechanism, a nozzle tip, and a guiding device. The handle mechanism employs a trigger that enables control of irrigation and vacuum / suction. Depression of a trigger in the trigger mechanism conveys status of vacuum / suction and irrigation to a user by providing increased resistance at different points of depression. When the trigger is in a home (undepressed) position, irrigation and vacuum / suction are turned off. When the trigger is in a fully depressed position, irrigation and vacuum / suction are turned on. When the trigger is in an intermediate position, irrigation may be turned on, while vacuum / suction remains turned off. The nozzle includes one or more irrigation ports positioned at a distal end of the nozzle and having an irrigation port departure angle of 30 to 60 degrees for directing irrigation fluid forward and laterally from the distal end of the nozzle. The guiding device is configured to be removably positioned in the nozzle for receiving a debris fragmentizing device, such as a laser device. The guiding device is configured to prevent an unintended movement of the fragmentizing device when the fragmentizing device is positioned in the nozzle while allowing fluid and debris to flow past the fragmentizing device and through a vacuum tube.

Kidney stone removal system is disclosed having components including a handle mechanism, a nozzle tip, and a guiding device. The handle mechanism employs a trigger that enables control of irrigation and vacuum / suction. Depression of a trigger in the trigger mechanism conveys status of vacuum / suction and irrigation to a user by providing increased resistance at different points of depression. When the trigger is in a home (undepressed) position, irrigation and vacuum / suction are turned off. When the trigger is in a fully depressed position, irrigation and vacuum / suction are turned on. When the trigger is in an intermediate position, irrigation may be turned on, while vacuum / suction remains turned off. The nozzle includes one or more irrigation ports positioned at a distal end of the nozzle and having an irrigation port departure angle of 30 to 60 degrees for directing irrigation fluid forward and laterally from the distal end of the nozzle. The guiding device is configured to be removably positioned in the nozzle for receiving a debris fragmentizing device, such as a laser device. The guiding device is configured to prevent an unintended movement of the fragmentizing device when the fragmentizing device is positioned in the nozzle while allowing fluid and debris to flow past the fragmentizing device and through a vacuum tube.

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.

The invention discloses a kidney stone prediction and early screening assisting method based on a machine learning model. The kidney stone prediction and early screening assisting method comprises the steps of S1, data integration; s2, preprocessing the data; s3, model training and prediction; and S4, outputting a diagnosis result and a treatment suggestion. Various vital sign data of a patient can be collected, the data are combined to form a personal health information file of the user, the obtained data are adjusted, the model is fitted, the system is used for conducting preliminary diagnosis and screening on kidney stone, the medical history of the patient can be integrated, data classification based on the vital sign data of the user and the model can be conducted, and the diagnosis accuracy of the kidney stone can be improved. And a doctor is helped to adjust the lifestyle of the user so as to avoid the formation of kidney stones.

The invention discloses a kidney stone detection system based on an SCC-YOLOX model, and belongs to the technical field of kidney stone intelligent detection.The system comprises a backbone network (Backbone), a neck network (Neck), a detection head (Head), an SE attention module, a CA attention module, a CBAM attention module and an error correction logic judgment module.The kidney stone detection system based on the SCC-YOLOX model is based on a YOLOX model network structure and combines various attention mechanisms, and the kidney stone detection accuracy is improved. The method aims at improving feature extraction capability and detection performance, effectively enhances fusion of feature expression capability and multi-scale semantic information by introducing SE, CA and CBAM attention modules, remarkably improves accuracy and efficiency of kidney stone detection, and reduces model parameter quantity, reduces calculation complexity and improves operation efficiency while keeping integrity of detection information. The built-in error correction logic judgment module realizes further investigation by identifying a specific scene with misclassification so as to improve the performance of the model and reduce the risk of kidney stone misdiagnosis.

The invention discloses a prediction method for kidney stone prognosis based on CT imaging omics, and relates to the field of medicine. Comprising the following steps that CT images and clinical data are collected, retrieval is conducted through a hospital medical record system, clinical information is collected, and the CT images are scanned through a scanner; cT image processing and feature extraction are carried out, calculus areas are sketched layer by layer on all cross sections of the CT image, information is recorded, and then feature extraction is carried out; and image omics feature screening and model construction: extracting image omics features from each original CT image. According to the method, CT image features and clinical prediction factors are combined, a clinical-image omics model is developed and verified, a repeatable, non-invasive, non-invasive and safe preoperative prediction method is provided, the calculus removal success rate of a kidney stone patient after flexible ureteroscope lithotripsy can be accurately evaluated, and the calculus removal success rate of the kidney stone patient after flexible ureteroscope lithotripsy is improved. And a clinician can be assisted to make a clinical decision and implement precise medical treatment.

The invention discloses a device for filtering broken kidney stone and urine, which comprises a filter box, the top of the filter box is provided with a feed hopper communicated with the filter box, the inner cavity of the filter box is movably connected with a filter screen, the right side of the upper surface of the filter box is provided with a fixed box, and the fixed box is internally provided with a lifting mechanism for adjusting the height of the filter screen. A sealing box is installed on the outer wall of the right side of the filtering box, a broken kidney stone collecting box is slidably connected into the sealing box, a back washing component is arranged in an inner cavity of the filtering box and located under the filtering net, the back washing component comprises a rotationally-connected liquid supply pipe, and multiple sets of communicated spray heads are arranged on the liquid supply pipe; and the liquid supply pipe is communicated with the liquid storage tank through the liquid supply assembly. The filter screen and the inner wall of the filter box are flushed through the back flushing component, urine of a previous patient is prevented from remaining on the filter screen, the precision of subsequent kidney stone breaking and urine test results is improved, and the accuracy of medical detection analysis is improved.

Kidney stone removal system is disclosed having components including a handle mechanism, a nozzle tip, and a guiding device. The handle mechanism employs a trigger that enables control of irrigation and vacuum / suction. Depression of a trigger in the trigger mechanism conveys status of vacuum / suction and irrigation to a user by providing increased resistance at different points of depression. When the trigger is in a home (undepressed) position, irrigation and vacuum / suction are turned off. When the trigger is in a fully depressed position, irrigation and vacuum / suction are turned on. When the trigger is in an intermediate position, irrigation may be turned on, while vacuum / suction remains turned off. The nozzle includes one or more irrigation ports positioned at a distal end of the nozzle and having an irrigation port departure angle of 30 to 60 degrees for directing irrigation fluid forward and laterally from the distal end of the nozzle. The guiding device is configured to be removably positioned in the nozzle for receiving a debris fragmentizing device, such as a laser device. The guiding device is configured to prevent an unintended movement of the fragmentizing device when the fragmentizing device is positioned in the nozzle while allowing fluid and debris to flow past the fragmentizing device and through a vacuum tube.

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 present invention relates to methods and systems for detecting the presence and concentration of biomarkers associated with kidney stone formation may be used to determine personalized treatment pathways in a subject. Nuclear magnetic resonance (NMR) spectroscopy may be a valuable tool for detecting various biomarkers associated with various disease states. A biological sample obtained from a subject may be examined using NMR spectroscopy to determine the presence and concentration of associated biomarkers.

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 present disclosure is directed to a medical device. Systems and methods are provided for utilizing a laser to break a kidney stones into smaller fragments and / or dust, and removing particles, stone fragments and / or stone dust from a patient. The medical device may include a delivery device including a tube, and an elongate member having a distal end, a proximal end, and a lumen extending between the proximal end and the distal end, wherein the elongate member is configured to move axially relative to the tube and apply suction through the distal end.

The invention relates to the technical field of health management, in particular to an ultrasonic image dynamic recognition-based liver, gall and kidney stone auxiliary diagnosis method, which comprises the following steps of: deploying a recommended sports diet monitoring server, collecting sports nutrition data for analysis and processing, constructing a sports nutrition mind map, and constructing a health management system; deploying an ultrasonic image scanner to acquire feature data of calculus personnel and outputting a calculus risk behavior set; mapping the obtained calculus risk behavior set to a motor nutriology mind map, and outputting a suggested mapping text to judge whether the calculus risk behavior set is unreasonable or not; collecting medical record checking data associated with a calculus person, analyzing and processing a calculus risk behavior set passing checking, and judging whether to output early warning data or not based on a contrastive analysis record; and collecting immune evaluation data of the associated calculus person in the sports diet monitoring time, deploying adaptive correction data, and performing reply processing. According to the invention, health management can be effectively implemented, so that liver, gall and kidney stones of patients can be effectively relieved.

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.