11 results about "Diagnostic quality" patented technology

State of the art mechanisms being used for achieving diagnostic-quality images under low-dose settings for general CT imaging have the disadvantages that CT images are fixed during the optimization process to generate perfusion maps, which can lead to suboptimal CT images with respect to the perfusion maps generated, although they might appear spatially smooth or denoised. The disclosure herein generally relates to Computer Tomography (CT) scanning, and, more particularly, to a method and system for CT image reconstruction. The system performs modelling an optimization problem for joint estimation of a set of structural CT images and a perfusion map, and further solves the optimization problem for the reconstruction of the CT images of a subject.

This invention discloses an automatic cardiac ultrasound recording system and method with anti-distortion capabilities. The method includes: acquiring synchronized cardiac ultrasound image frames and probe motion state data; extracting explicit anatomical quality features and implicit spatiotemporal fusion features; generating predicted spatiotemporal features based on historical implicit features; obtaining a section quality deviation index by combining acoustic coupling quality indices; dynamically determining stable and distortion boundaries based on the deviation index within a sliding window; classifying the current frame as stable, transitional, or distorted; recording when the frame is stable and the phase meets the conditions; recording when the frame is transitional and the predicted and current features are adaptively fused and compensated based on observational uncertainty; and pausing recording and providing attribution prompts when the frame is distorted. This invention achieves precise decoupling of probe motion and cardiac motion through IMU and image fusion, and employs a dynamic threshold and residual calibration mechanism to effectively improve the continuity and diagnostic quality of automatic recording, making it suitable for intelligent control of cardiac ultrasound examinations.

The subject matter includes systems and methods for a deep learning technique applied to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) scans. The disclosed aims to reduce the dosage of gadolinium-based contrast agents (GBCAs) while maintaining accurate detection and enhancement of BBB openings. A spatiotemporal network (ST-Net) is introduced, combining spatial and temporal networks, allowing for the extraction of diagnostic quality images with reduced GBCAs dosage.

The invention discloses an artifact-removing shaping pillow device for magnetic resonance scanning. The artifact-removing shaping pillow device comprises a shaping pillow body, a temperature control circulating device and a controller. A low-temperature thermoplastic core, a microcirculation pipe network used for circulating heat conduction liquid and a distributed sensing network used for monitoring the temperature in real time are arranged in the moldable pillow body. The temperature control circulating device comprises a bidirectional heat exchange module used for heating and refrigerating the heat conduction liquid and a circulating pump connected with the bidirectional heat exchange module. The controller can accurately control the temperature control circulating device through closed-loop feedback according to real-time multi-point temperature data provided by the sensing network, so that rapid, uniform and safe heating softening and cooling shaping of the thermoplastic core are realized. According to the invention, the plastic pillow body is utilized to form an individualized support fitting the neck curve for a patient, and an air gap in a neck scanning area can be filled, so that magnetic sensitivity artifacts are inhibited, and the diagnostic quality of magnetic resonance images is remarkably improved.

A system including a diagnostic-quality CT scanner for imaging a patient, the diagnostic-quality CT scanner having an imaging isocenter and a radiation therapy device positioned adjacent the diagnostic-quality CT scanner, the radiation therapy device including a gantry carrying a radiation therapy beam source and having a radiation therapy isocenter separate from the imaging isocenter of the diagnostic-quality CT scanner. The system including a couch configured to position the patient for imaging and for radiation therapy by translating the patient between the diagnostic quality CT scanner and the radiation therapy device.

To provide devices and methods that can help enable real-time, full-color, diagnostic-quality resolution, direct intravascular visualization of cerebrovascular lesions.SOLUTION: The sheath catheter 102 may be advanced toward a cerebrovascular lesion. The balloon at the tip can be inflated. An angioscope 104 may be inserted through the working lumen for viewing. The Sheath Catheter can have a stepped down lateral profile and can extend the working channel a distance beyond the balloon. The dual concentric lumen structure can include an inner body and an outer body defining an inflation lumen therebetween, with one or more portions of one or more layers being stretched or cut or both, such as to provide bending flexibility. Reflow techniques may be used to help bond the layers together.SELECTED DRAWING: Figure 1

Disclosed are systems and method for automated magnetic resonance elastography (MRE) quality control and stiffness measurements. The exemplary systems and methods described herein utilize deep learning (DL) to reduce inter-observer variability, improve processing time and workflow constraints, and assist operators with troubleshooting based on artifact sources.

This invention provides a method for preventing disconnection of a wireless handheld ultrasound device. The wireless handheld ultrasound device's ultrasound signal imaging process within a work cycle includes at least a first-type task phase. The method includes: Step S1, real-time monitoring of the wireless communication activity of the wireless communication module of the wireless handheld ultrasound device and acquisition of multiple communication timing information within the work cycle; Step S2, comparing the work timing information of the first-type task phase in the current work cycle with the communication timing information, and adjusting the work cycle when conflicts arise between the work timing information and the communication timing information. By adjusting the timing of highly interfering tasks, the timing of ultrasound imaging and communication timing are prevented from interfering with each other, resulting in a stable uploaded image frame rate, improved user experience, and enhanced diagnostic quality.

The invention relates to the technical field of physiological signal diagnosis, and discloses a real-time monitoring and judging system for sleep period arrhythmia, which comprises a sensor for synchronously acquiring physiological signals and motion signals and a processor, and is characterized in that the motion signals are used for carrying out first gating to eliminate motion pollution; calculating a signal quality index of the resting data segment through a signal quality calculation module, and dynamically setting a diagnostic quality threshold value for second gating by using a reference signal captured by a dynamic self-calibration module in a motion-resting conversion event; finally, the arrhythmia judgment module only executes arrhythmia judgment on the data segments passing through double gating, the system avoids double interference of motion artifacts and low-quality signals in a resting state through serial double gating, a unique dynamic self-calibration mechanism of the system translates the motion interference into an individualized calibration beacon, and the accuracy of the system is improved. Therefore, the problem that the static threshold loses efficacy due to individual differences is solved, and the diagnosis reliability is ensured.

The present application relates to a biliary tract cancer prediction method and system based on iterative self-consistency and large model verification, relating to the field of artificial intelligence, comprising obtaining electronic medical record text data of a patient to be predicted; the present application inputs a prompt word sequence into a current base large language model to generate an independent reasoning path set, adopts a majority voting mechanism to select positive samples and negative samples, constructs candidate data pairs, introduces a verification large language model to verify the medical logic rationality of the positive samples, guarantees the diagnosis quality through a double mechanism, improves the accuracy and reliability of the diagnosis reasoning, supervises and fine-tunes the current base large language model, optimizes a comparison loss function to obtain an updated base large language model, realizes continuous iterative optimization of the diagnosis logic, inputs the structured prompt word sequence of a new patient to be diagnosed into the final base large language model, generates an optimal reasoning path and a diagnosis conclusion, and outputs a thought chain reasoning result containing medical logic.

Disclosed in an integrated retinal imaging system designed to enable high-quality, diagnostic image capture with minimal operator intervention. The system can implement a dual-stage Holistic Quality Assessor (HQA), with HQA-1 performing real-time, holistic quality assessments on infrared or near infrared image frames to detect optimal capture conditions, and HQA-2 verifying the diagnostic adequacy of a captured color image. Both HQA-1 and HQA-2 can leverage machine learning or deep-learning models executed on a local hardware accelerator and are configured to provide low-latency and accurate evaluations. By combining dual-stage quality assessment with real-time capture optimization, the system can enable reliable, diagnostic-quality image capture across various clinical settings and user experience levels.