20 results about "Bladder volume" patented technology

The present application belongs to the field of computer vision and medical image processing, and particularly relates to a multi-view bladder volume measurement method based on improved YOLO detection and positioning. The method comprises the following steps: step 1, pre-processing of bladder ultrasound image data; step 2, establishing a joint neural network model for view classification and bladder positioning; step 3, detection of bladder ultrasound image cross-section and longitudinal section; step 4, scale detection; and step 5, bladder volume calculation and correction. The present application realizes an automatic method integrating multi-view ultrasound image recognition and bladder volume measurement, so as to reduce the dependence on professional prior knowledge and lower the operation threshold of non-professional doctors; at the same time, the method can provide relatively objective diagnostic reference data under different equipment environments and image qualities, and improve the scientificity of auxiliary medical decision-making.

This image is a visualization of a patient's bladder, automatically and noninvasively observed using an ultrasound diagnostic device. Two sector transducers capture two cross-sectional images of the bladder, and bladder volume is calculated based on the images and displayed along with the cross-sectional image. A detailed explanation is provided below, based on the image. First, remove the probe (see reference image) from the cradle and press the power button. The home screen appears, along with the operation interface. The operation interface is divided into a status bar at the top and a main button area at the bottom. The status bar displays the time, number of images available, current ID, sound (ON / OFF), and battery level. The main button area displays various measurement modes, measurement data, settings, and ID setting options. The operation interface shows the positioning of the operator (orange circle) when operating the probe from the right side of a supine patient (white human pictogram) and when operating the probe from the left side. In this position, the probe, coated with ultrasound gel, is aligned with the patient's midline, approximately 3 cm above the pubic bone. The front of the display faces the operator. Image 1, showing the post-change image, represents a cross-sectional image obtained when the patient is standing on the right side of the operation image. Images 2 and 3, showing the post-change image, represent cross-sectional images obtained when the patient is standing on the left side of the operation image, and either one can be selected depending on the settings. In images 1 to 3, showing the post-change image, the body shape can be selected as needed using the "Body Shape Button," and the image brightness can be adjusted using the "Brightness" button. To return to the original state, select the home button.

The invention relates to the field of artificial urethral sphincter, in particular to a self-adaptive artificial urethral sphincter based on bladder capacity monitoring, comprising: a urethral closure unit for applying dynamically adjustable closure pressure on the urethra of a patient; the bladder monitoring unit is used for dynamically monitoring parameters related to the bladder filling state of the patient and generating a signal indicating the bladder filling state; and the implantable control unit is connected with the urethra closing unit and the bladder monitoring unit and is configured to receive the signal from the bladder monitoring unit and dynamically adjust the closing pressure applied to the urethra by the urethra closing unit according to the bladder filling state indicated by the signal. According to the embodiment of the invention, through intelligent adjustment of pressure application according to needs, the urethral tissue can bear high pressure only when the bladder is full or other necessary conditions are needed, and is in a low-pressure state for a long time, so that the total pressure load is reduced, and tissue atrophy and erosion caused by long-term ischemia are prevented.

This invention discloses a novel method and system for ultrasound measurement of bladder volume. The method includes: acquiring dense point cloud data of the bladder from CT scans, and generating a dataset of incomplete meridians simulating ultrasound based on the characteristics of ultrasound imaging; constructing a point cloud completion model based on deep learning, training the model using CT data to achieve the mapping from incomplete point clouds to dense point clouds; and using the Crust algorithm to perform three-dimensional reconstruction and volume calculation on the completed dense point cloud. This invention corrects the systematic errors of the ultrasound system by leveraging the high precision characteristics of CT data, achieving high-precision measurement of bladder volume under radiation-free and low-cost conditions. The measurement error can be controlled within 10%, making it suitable for rapid and accurate assessment of bladder volume before radiotherapy.

The invention provides an intelligent bladder volume control method, device and equipment based on bladder pressure monitoring, belongs to the technical field of data processing, and aims to solve the problem of poor precision of keeping the current bladder volume constant, adaptive bladder diversion control can be carried out according to the urine increment rule of a target patient after drinking water, and the accuracy of bladder volume control is improved. The volume of urine in the bladder can be always kept within a certain interval, so that the pressure in the bladder can be prevented from being too high, and the keeping precision of the bladder capacity can be improved to a certain extent.

The invention provides a urination early warning method and system for time sequence prediction based on a large language model, and the method at least comprises the following steps: S1, collecting bladder volume dynamic change data through a urine volume collection terminal in a non-contact manner, and transmitting the data to a mobile terminal APP through a Bluetooth transmission unit; s2, preprocessing the original volume data acquired by the urine volume acquisition terminal through the mobile terminal APP, and recording static characteristics of a user; s3, carrying out feature fusion on the preprocessed volume time sequence data and static features through a large language model prediction server, constructing a three-dimensional input matrix, carrying out prediction reasoning by utilizing a pre-trained large language model, and outputting a future urination time point; and S4, triggering early warning and reminding according to the prediction result and the real-time bladder capacity. The system at least comprises a urine volume collection terminal, a mobile terminal APP and a large language model prediction server. According to the method and the system, accurate prediction of the urination time in the future is realized through deep learning of individual historical data by a large language model.

An ultrasound diagnostic apparatus (1) includes an ultrasound probe (21); an inclination angle sensor (13) that detects an inclination angle thereof; an image acquisition unit (5) that acquires an ultrasound image; a bladder extraction unit (8) that extracts a bladder region from the ultrasound image; a feature quantity calculation unit (9) that calculates a feature quantity of the bladder region; a first measurement unit (10) that measures a first maximum diameter and a second maximum diameter of the bladder region from the feature quantity; a manipulation assist unit (11) that assists a user in a slide manipulation of the ultrasound probe (21) such that a scanning section indicates the first maximum diameter and the second maximum diameter; a second measurement unit (14) that measures a third maximum diameter of the bladder region orthogonal to the scanning section on the basis of the ultrasound image and the inclination angle at the assisted position; and a bladder volume calculation unit (15) that calculates a volume of the bladder.

Embodiments disclosed herein are directed to a self-learning bladder volume monitoring system. The system can include a bladder volume (BV) system configured to measure an electrical impedance of a bladder region of a patient and determine a volume of fluid disposed therein using an impedance to bladder volume model (“By model”). Further, the system can measure a total body water (“TBW”) for the patient and modify the BV model to account for variations in TBW within the tissues surrounding the bladder providing a more accurate bladder volume measurement. The system can include a “training unit” which can include one of a user input interface, an automatic urine output monitoring system, an ultrasound system, and an intrabladder pressure system configured to verify a volume of fluid within or voided from the bladder and train the BV model.

The invention relates to a method for detecting whether the bladder of a patient is full or not during radiotherapy, and the method comprises the steps: model preparation and transfer learning: obtaining a deep learning model which is trained on a CT image and is used for automatically segmenting an ROI, and carrying out the transfer learning fine tuning of the deep learning model through a CBCT image data set marked with the bladder ROI, a bladder segmentation model suitable for the CBCT image is obtained; image acquisition and preprocessing: acquiring a CBCT image of a patient and preprocessing the CBCT image; automatic segmentation and volume estimation: inputting the preprocessed CBCT image into a bladder segmentation model to obtain a segmentation result of the bladder ROI, and then calculating the volume of the bladder based on the segmentation result; and filling state judgment: based on the calculated bladder volume and the bladder volume preset by the treatment plan, calculating an overlapping degree index of the two so as to obtain a bladder filling state judgment result. According to the invention, accurate segmentation and volume estimation of the bladder area can be realized, the filling state is further judged, and an instant and objective basis is provided for formulation and adjustment of a radiotherapy scheme.

A case for a cartridge of a printer is disclosed. The case includes: a plurality of walls defining a bladder volume configured to receive a bladder of the cartridge and a neck interface of a front wall of the plurality of walls. The neck interface defines a neck aperture configured to receive a neck of the bladder. The case is a single continuous piece of material.

The application provides a kind of spatiotemporal dynamic big data analysis system and method based on wearable ultrasonic equipment, belongs to the cross technical field of medical equipment and big data analysis, including: wearable ultrasonic equipment, adhere to the lower abdomen of subject, for transmitting ultrasonic wave and receiving echo signal;Spatiotemporal dynamic big data analysis module is used to form spatiotemporal dynamic dataset according to echo signal and time stamp, is handled and analyzed based on bladder analysis model, automatically identifies bladder boundary, calculates bladder volume and bladder wall thickness and generates clinical impression;Display module and data transmission module.The beneficial effect is: realize the home monitoring of bladder function, reduce the number of patient hospitalization and outpatient follow-up frequency, reduce medical expenditure, simultaneously provide data support for telemedicine, optimize medical resource allocation.

The invention provides a closed-loop diagnosis and treatment method for bladder dysfunction, and relates to the technical field of biomedical monitoring and treatment. Comprising the following steps: acquiring a signal related to bladder filling through a non-invasive bladder volume measuring device, and analyzing the signal in real time to estimate the bladder volume; subsequently, the measuring device compares the estimated volume with a preset capacity threshold value and generates a trigger signal for activating an external excitation source when the volume reaches or exceeds the threshold value. The external excitation source outputs mechanical energy after receiving the trigger signal, and the mechanical energy is transmitted to the wireless nerve stimulator in the body in a wireless mode; and the stimulator converts the received mechanical energy into electric energy, and the electric energy is processed by the energy management circuit to generate an electric stimulation signal for regulating and controlling neural activity, so that the adjustment of the bladder function is realized. The defects that in a traditional diagnosis and treatment scheme, monitoring continuity is poor, intervention depends on professionals, individualized regulation and control cannot be achieved, and a closed-loop control mechanism is lacked are effectively overcome.

Methods and systems for ultrasound-based urodynamic evaluation are presented in the present disclosure. Pre-void and post-void ultrasound data of a bladder is acquired, in addition to a dynamic acquisition during voiding on a sagittal plane that encompasses the bladder, bladder neck and proximal urethra. The dynamic acquisition may be an ultrasound cine scan or a uroflowmetry measurement during voiding. Using semiautomatic segmentation, the volumes are quantified and virtual models are generated. Similarly, the ultrasound cine sagittal images are segmented to determine the deformation pattern of the bladder during voiding. Using an algorithm, a volume interpolation between pre and post void volumes is performed using the deformation profile obtained from the dynamic sagittal images as a constraint. Resolved bladder volumes are then analyzed using a computational fluid dynamics algorithm to derive flow rates and pressures and to calculate indices of contractility (BCI) and bladder obstruction (BOOI).

The invention relates to the technical field of trachea cannulas, and discloses a disposable inflation-free trachea cannula which comprises a cannula body, an insertion head arranged at the front end of the cannula body and a connector arranged at the rear end of the cannula body, an air bag is arranged on the outer wall of the cannula body in a sealed mode, and the air bag is filled with memory sponge; the other end of the air pipe is connected with a three-way valve, and the three-way valve is connected with an air extractor. According to the trachea cannula, the mode that a traditional trachea cannula depends on continuous external inflation for fixation is abandoned, and intubation can be smoothly completed only through single-time air exhaust to enable the memory sponge to be shrunk to reduce the size of the air bag; after implantation, the three-way valve is opened, the memory sponge automatically expands and resets depending on the memory characteristic of the memory sponge, the air bag is driven to be attached to the air channel to achieve fixation, continuous inflation and pressure maintaining are not needed, the air bag pressure does not need to be repeatedly adjusted, operation steps are simplified, the device is suitable for various clinical scenes such as emergency intubation and bedside conventional intubation, and medical workers are low in starting difficulty; the whole set of operation can be completed by one person, and the intubation efficiency is greatly improved.

The invention provides a noninvasive bladder function monitoring method and system based on time sequence prediction, and the method comprises the steps: training a bladder pressure prediction model based on the clinical data of a patient and the UDS examination data of the patient; obtaining water drinking urethral catheterization data, heart rate and environment temperature and humidity of a patient to be monitored, and inputting the data into the trained urine generation rate prediction model to obtain real-time bladder volume data; and inputting the clinical data of the to-be-monitored patient and the predicted bladder volume data into the bladder pressure prediction model to obtain a bladder pressure prediction value of the to-be-monitored patient. By collecting UDS images and diagnoses of a large number of patients and combining clinical data of the patients, drinking urine catheterization data, heart rate and environment temperature and humidity, the prediction model is trained, the bladder pressure of the patients at different disease stages and under different bladder filling degrees is predicted, a non-invasive AI UDS monitoring means is provided for the patients, and the accuracy of bladder pressure monitoring is improved. And a patient is helped to better manage the bladder in a home state.

A bladder volume monitoring system based on Advanced Reduced Instruction Set Computing Machines (ARM), characterized in that it comprises: a three-chamber urinary catheter (2), an air supply channel (26), a fluid supply channel (25), and a fluid drainage channel (27); wherein one end of the three-chamber urinary catheter (2) is positioned inside a bladder (24) during use, and the other end of the three-chamber urinary catheter (2) is provided with three openings, each being an air opening (21), a fluid supply opening (22), and a fluid drainage opening (23); wherein the air inlet end of the air supply channel (26) is connected to an external air source, and the air outlet end of the air supply channel (26) is connected to the air opening (21);wherein the fluid inlet end of the fluid supply channel (25) is connected to an external fluid container and the fluid outlet end of the fluid supply channel (25) is connected to the fluid supply port (22); wherein the fluid inlet end of the fluid drainage channel (27) is connected to the fluid drainage port (23) and the fluid outlet end of the fluid drainage channel (27) is connected to an external container; wherein the end of the three-chamber urinary catheter (2) located inside the bladder (24) is provided with several three-chamber urinary catheter fluid inlet ports (22a) connected to the fluid supply port (22) and a three-chamber urinary catheter fluid drainage port (23a) connected to the fluid drainage port (23);wherein the end of the three-chamber urinary catheter (2) located inside the bladder (24) is further equipped with a balloon (20), and the balloon (20) is connected to the air opening (21); wherein a sensor (16) is arranged on the fluid supply channel (25), and the sensor (16) serves to monitor the pressure in the fluid supply channel (25) in order to determine the pressure in the bladder (24).

This application discloses a method for predicting bladder volume between and within radiotherapy fractions, belonging to the field of precision radiotherapy. The method includes: acquiring a sequence of fan-beam CT images of multiple completed treatment fractions for a patient, including pre-treatment images, pre-exit images, and post-exit images for each fraction; segmenting the images into bladder regions to construct a temporal volume dataset; determining the predicted bladder volume before the next treatment fraction using an inter-fraction prediction model; and determining the predicted bladder volume at a specified time point during the current treatment fraction using an intra-fraction dynamics model. The input to the inter-fraction prediction model includes at least one of volume sequence, water intake information, and extracted features; the input to the intra-fraction dynamics model includes at least one of the current pre-treatment bladder volume and daily water intake information. This application achieves dual-timescale prediction of bladder volume, providing a prospective decision-making basis for adaptive radiotherapy and improving the accuracy and safety of radiotherapy.

This invention relates to the technical field of endotracheal intubation and discloses a disposable, non-inflatable endotracheal tube, comprising a tube body, an insertion head at the front end of the tube body, and a connector at the rear end of the tube body. An air bladder, filled with memory foam, is sealed to the outer wall of the tube body. An aspiration tube is connected to the air bladder, and a three-way valve is connected to the other end of the tube, which is connected to an aspiration device. This endotracheal tube abandons the traditional method of relying on continuous external inflation for fixation. Only a single aspiration is needed to shrink the memory foam and reduce the air bladder volume, allowing for successful intubation. After insertion, opening the three-way valve causes the memory foam to automatically expand and reset due to its memory properties, causing the air bladder to conform to the airway for fixation. This eliminates the need for continuous inflation and pressure maintenance, as well as repeated adjustments to the air bladder pressure. The operation is simplified, adaptable to various clinical scenarios such as emergency intubation and routine bedside intubation. It is easy for medical staff to learn, and a single person can complete the entire operation, significantly improving intubation efficiency.

The invention discloses a wearable ultrasonic device for bladder capacity monitoring and a preparation method thereof, and relates to the technical field of medical instruments and bioelectronics, the device comprises a flexible ultrasonic sensor and a signal processing unit; the flexible ultrasonic sensor includes: a flexible substrate layer; the ultrasonic sensing array is arranged on the flexible substrate layer and is used for acquiring A-type ultrasonic echo signals of a bladder area; the acoustic matching layer is adhered to the ultrasonic sensing array; an acoustic lens structure is integrated in the acoustic matching layer; the flexible circuit module is electrically connected with the ultrasonic sensing array and is used for collecting and transmitting A-type ultrasonic echo signals; the signal processing unit is connected with the flexible circuit module, and is used for processing the A-type ultrasonic echo signal, performing interval classification on the bladder capacity based on a machine learning model, and determining a classification result; the whole wearable ultrasonic device is of a flexible attached structure, and the bladder capacity can be monitored more accurately.

A patient turning device for a patient support apparatus. The patient turning device includes a first and second bladder assembly each including a plurality of layers and seals defining a bladder volume. The bladder volumes are selectively inflatable with fluid to expand the respective bladder assembly, and consequently move a patient support surface of the patient support apparatus. A portion of a lower layer of the first bladder assembly and a portion of an upper layer of the second bladder assembly define an overlapping region of the bladder volumes. The patient turning device is coupled to an underside of a carrier sheet and positioned between a crib assembly and a bottom cover. An augmenting feature is configured to resiliently expand as at least one of the first and second bladder assemblies receives the fluid to move at least a portion of the crib assembly away from a patient support deck.