24 results about "Cardiac imaging" patented technology

The invention discloses an electrophysiological signal fusion method and device, relates to the technical field of biomedicine, and mainly aims to solve the problem of low cardiac imaging evaluation accuracy caused by poor effectiveness of existing electrophysiological signal fusion. The method includes the steps that electrophysiological signals obtained after cardiac organs are collected and subjected to active magnetic field compensation and passive magnetic field compensation are obtained, and active magnetic field compensation signals of active magnetic field compensation are completed by controlling a main control magnetic field source based on a deep neural network model; a passive magnetic field compensation signal of the passive magnetic field compensation is completed based on residual magnetic field data modeling; screening effective signals from the electrophysiological signals, and performing inversion reconstruction on the effective signals to obtain current density distribution; cross-modal fusion is conducted on the electrophysiological signals, the current density distribution and the electrocardiosignals through a deep learning model after model training is completed, a signal fusion result is obtained, and the deep learning model is trained based on Maxwell constraints.

In emission imaging, one, two, or a few topograms without a full CT scan are used to localize, such as through triangulation, and / or generate an attenuation map, such as based on model fitting. A limited radiation exposure, rather than a longer, larger full CT exposure, is needed to localize and / or provide attenuation correction for emission imaging, such as cardiac SPECT imaging.

A method for motion estimation in CT systems is provided. The method includes dividing projection data, obtained by scanning a heart using the CT system, into a plurality of partial-angle-reconstruction (PAR) bins, reconstructing a plurality of PAR volumes from the PAR-binned projection data, obtaining, based on the plurality of reconstructed PAR volumes, a number of short-scan volumes, determining, based on the obtained number of short-scan volumes, a plurality of nodes throughout the heart, estimating, for each of the determined plurality of nodes, a plurality of model parameters of a motion model, and generating, based on the plurality of model parameters estimated for each of the plurality of nodes, parameters of a global motion model at each voxel of a volume of the heart. The method also includes reconstructing, based on the generated motion parameters of the global motion model at each voxel of the volume of the heart, a motion-compensated short-scan volume.

The present invention discloses a sequential scanning DECT cardiac imaging method based on AIGC conditional generation, including sequential CT scanning of projection data of different phases and high and low energy levels of the heart, using the projection data to perform FDK reconstruction to obtain image domain data of high and low energy levels, selecting high and low energy level organ images in a relatively static state in the image domain to train a conditional generation network model Energy-GAN, using low-energy image layers of moving organs as input conditions of Energy-GAN to generate high-energy image layers in the same motion state, and finally performing image domain material decomposition on the generated high-energy image and the corresponding low-energy image, and using a pre-trained diffusion model to denoise the material decomposition image. The present invention realizes sequential scanning DECT cardiac imaging, effectively reducing the material decomposition artifacts caused by cardiac motion and the noise generated by image domain material decomposition without performing flexible 3D image registration.

The application relates to a magnetic resonance imaging method, device, computer equipment, storage medium and computer program product. The method comprises the following steps: in a first cardiac cycle, a characteristic electrocardio signal of a detection object is identified, a first sequence pulse is applied to the detection object after a preset delay time of identifying the characteristic electrocardio signal, and the first sequence pulse is used for reversing a longitudinal magnetization vector of the detection object; after the first sequence pulse is applied, a second sequence pulse of a target phase mode is applied to the detection object after a recovery time, and an initial cardiac imaging set is acquired, wherein the target phase mode is one of at least two different phase modes, and different target phase modes correspond to different positions of artifacts in the initial cardiac imaging sets; and the initial cardiac imaging sets obtained in each first cardiac cycle are subjected to first registration processing to obtain a cardiac imaging. The method can effectively weaken the artifacts in cardiac delayed enhancement imaging, and does not increase additional operations and additional scanning time.

A system and method for human heart modelling to create a dynamic virtual model of heart that can be used for diagnosis and determining suitable therapy. The dynamic virtual model can be created using 2D or 3D echo images or video clips obtained from ultrasound reversal wave data. Arbitrary pixels or voxels in the echo images are tracked phase-by-phase per cardiac cycle. From this, original reversal wave equation ρp attached to the arbitrary pixel or voxel is obtained. Then is generated a deformable map fp with an equation of curve passed from the arbitrary pixel or voxel within the cardiac cycle determined by solving Lagrange-Euler equations. Finally, new 2D or 3D images with improved spatial resolution can be obtained that are used for the human heart modelling.

This invention discloses a heart failure readmission risk assessment system based on cardiac imaging feature analysis, belonging to the field of cardiac imaging analysis technology. By analyzing speckle texture features in ultrasound images and combining them with respiratory phase and image quality information, a dynamic and regular quantitative index is generated, thereby achieving accurate risk assessment. It can identify potentially high-risk patients in advance, even those with normal or mildly abnormal ejection fractions, and effectively addresses the impact of respiratory phase changes and image quality interference on assessment results. By weighted fusion of image quality and physiological state information, the stability and accuracy of the assessment results are improved, making it particularly suitable for primary healthcare institutions. This invention provides a more objective and accurate risk assessment, offering a scientific basis for doctors to develop personalized treatment plans, thereby significantly improving the early identification and treatment outcomes of heart failure patients.

This invention discloses an automatic identification and classification method for scarred myocardium based on cine magnetic resonance imaging (CMRI) and deep learning. After preprocessing cardiac cMRI images, the method extracts the relative motion and imaging features of the left ventricular myocardium. A multimodal feature fusion network is then used for training and prediction to identify and classify five different types of scarred myocardium. The extraction of relative motion and imaging features enables an accurate and detailed description of the state of scarred myocardium. The multimodal feature fusion network model captures the compensatory effects of long-distance scarred myocardium movement, the non-rigid deformation motion patterns of the myocardium, and the spatiotemporal relationship between myocardial motion and morphology. This invention achieves high efficiency and accuracy in identifying and classifying scarred myocardium, saving doctors time and effort in diagnosing cardiovascular diseases leading to scarred myocardium, reducing patient suffering, and facilitating a more stable and simpler examination and diagnostic method.

The present invention provides a system for detecting myocardial damage based on imaging characteristics, which comprises an image acquisition module, a feature extraction module, a data processing module, and a report generation module. The image acquisition module is configured to acquire high-resolution cardiac imaging data; the feature extraction module is configured to extract cardiac structural and functional feature information from the acquired imaging data; the data processing module is configured to analyze and identify myocardial damage based on the extracted feature information; the report generation module is configured to generate medical reports for physicians regarding myocardial damage. The present invention provides a more comprehensive and accurate assessment of myocardial damage by performing a comprehensive analysis of the patient's cardiac imaging data, thereby enhancing the accuracy and effectiveness of medical diagnosis.

The invention discloses a heart CT imaging method and device, electronic equipment and a storage medium. The heart CT imaging method comprises the steps of obtaining a plurality of reconstructed images corresponding to a plurality of periods based on original heart scanning data; determining an initial motion field of scanning angles corresponding to the plurality of reconstructed images based on a motion field estimation model; fitting the initial motion field to obtain a target motion field of all scanning angles; and performing motion compensation on the heart images corresponding to the plurality of scanning angles based on the target motion field to obtain a plurality of compensation images, and fusing the plurality of compensation images to obtain a target image. According to the heart CT imaging method, the deep learning network is combined with the multi-phase image to estimate the operation field, the heart motion field can be estimated more accurately, and the imaging effect is better.

A cardiac angiography analysis method, an angiography data processing method and an ultrasonic imaging device, the method comprising: when the heart of a target object is in a resting state, injecting a contrast agent to the heart of the target object, emitting a first ultrasonic wave to the heart containing contrast agent microbubbles, and generating a first angiography image; acquiring a first myocardial angiography parameter of the myocardial region of interest as a resting parameter based on the first angiography image; when the heart of the target object is in the load state, a contrast agent is injected into the heart of the target object, second ultrasonic waves are emitted to the heart containing contrast agent microbubbles, and a second contrast image is generated; acquiring a second myocardial angiography parameter of the myocardial region-of-interest as a load parameter based on the second angiography image; and determining reserve parameters of the myocardial region of interest based on the resting parameters and the load parameters, and outputting the reserve parameters or information reflecting the reserve parameters. According to the method, the reserve function and dynamic change of the myocardium can be accurately evaluated.

A catheter-based ultrasound imaging system configured to provide a full circumferential 360-degree view around an intra-vascular / intra-cardiac imaging-catheter-head by generating a three-dimensional view of the tissue surrounding the imaging-head over time. The ultrasound imaging system can also provide tissue-state mapping capability. The evaluation of the vasculature and tissue characteristics include path and depth of lesions during cardiac-interventions such as ablation. The ultrasound imaging system comprises a catheter with a static or rotating sensor array tip supporting continuous circumferential rotation around its axis, connected to an ultrasound module and respective processing machinery allowing ultrafast imaging and a rotary motor that translates radial movements around a longitudinal catheter axis through a rotary torque transmitting part to rotate the sensor array-tip. This allows the capture and reconstruction of information of the vasculature including tissue structure around the catheter tip for generation of the three-dimensional view over time.

The invention relates to a spectrum distinguishing heart CT (computed tomography) imaging method. In the method, first spectrally differentiated CT projection measurement data relating to the heart of the patient in a first time interval during which a contrast agent, preferably iodine, is located predominantly in the chamber and / or in the blood vessel of the heart is received, the first time interval comprising the diastolic period of the heart. In addition, second spectrally distinguished CT projection measurement data is received which is related to the heart of the patient in a later second time interval during which the contrast agent is located predominantly in the muscular tissue of the heart, where the second time interval comprises the systolic period of the heart. First monoenergetic image data is calculated for a first energy value based on the first spectrally distinguished CT projection measurement data, and second monoenergetic image data is calculated for the first energy value based on the second spectrally distinguished CT projection measurement data. The invention further relates to an image generation device and a computed tomography system.

An ultrasonic transducer multilayer structure, including: a semiconductor layer stack defining a diode, a micro-machined ultrasonic transducer, MUT, layer stack being electrically in series with said diode and comprising a first electrically conductive layer disposed at least partly on the diode, a cavity extending over a region comprising at least a portion of the semiconductor layer stack and the first electrically conductive layer, wherein the MUT layer stack comprises a membrane extending at least partly over said region. The ultrasonic transducer multilayer structure may be used in a sensor apparatus for measuring at least one characteristic of an object. The sensor apparatus is used for medical imaging, such as cardiac imaging, obstetrics, gynecology, abdominal imaging, intravascular imaging, and mammography, or non-destructive testing (NDA), fingerprint sensors, range finders, gesture recognition, ultrasonic haptic feedback, ultrasonic communication or MEMs speakers.

A computer-implemented method for motion compensation of medical imaging data includes estimating, via a processor, non-periodic motion of a myocardium of a heart due to respiration and / or other body movements throughout a positron emission tomography (PET) scan based on list-mode emission data acquired during the PET scan of the heart of a subject. The method also includes performing, via the processor, event-by-event motion-corrected list-mode reconstruction on the list-mode emission data to generate cardiac images with the non-periodic motion removed.

The invention provides a percutaneous patent foramen ovale plugging interventional operation robot system, and relates to the technical field of patent foramen ovale plugging interventional operations. The interventional surgery robot system is configured to obtain cardiac image data and occluder structure data, perform occlusion positioning and shunt analysis, and determine an occlusion mounting position area and unclosed shunt data; real-time placement position information of the plugging device is obtained, real-time plugging positioning analysis is carried out in combination with the plugging installation position area, and real-time positioning plugging result information is formed; on the basis of the real-time positioning plugging result information, real-time shunting data of the plugging area is obtained, plugging effect analysis is carried out in combination with the unclosed shunting data, and plugging effect analysis result information is formed; according to the interventional operation robot system, real-time monitoring of the overall effect of the plugging device from installation to after installation is achieved by collecting and analyzing real-time installation data of the plugging device, the success rate of the operation is further increased, and the efficiency of the whole clinical operation is improved.

The present invention relates to a heart tissue ablation device comprising a charged particle emitting system 1, a control system 2 for instructing the accelerator and beamline when to create the beam and what its required properties should be, a patient positioning and verification system, an ultrasound cardiac imaging system 3 performed on the patient, able to track the target movement, a computer program to determine and record the safe motion margins, the treatment plans for one or more motion phases and a computer program to regulate the control system 2 to load the correct irradiation plan according to the motion phase and if the position of the target is inside of the position margin, the irradiation is enabled and if the position of the target is outside of the position margin, the irradiation is disabled.

This invention belongs to the interdisciplinary field of medicine and computer science, and discloses a view localization method in three-dimensional cardiac images based on relative position regression. The method resamples, aligns, extracts the region of interest (ROI) of the heart, and standardizes the intensity of the input three-dimensional cardiac CT / MRI data, automatically generating two-dimensional slices with arbitrary orientation and position and their rigid pose parameters. A self-supervised pre-training encoder-decoder network is performed based on a random occlusion reconstruction task, outputting a low-dimensional representation vector for any slice. Within the same three-dimensional cardiac image, three-point labels with relative displacement are constructed for any slice pair, and a relative position regression mapping network is trained to learn relative geometric relationships in a unified latent coordinate space. The method receives reference view prompts, performs multi-step navigation and multi-initial position integration in the target three-dimensional cardiac image, outputs the planar parameters, DICOM coordinates, and quality score of the target view, and supports integration with clinical workstations or robot navigation systems.

A system and methods for machine learning driven contouring of cardiac ultrasound data is provided. A system may receive cardiac imaging data generated by an ultrasound device directed at a left ventricle of a heart. The imaging data may include a time dimension and a plurality of spatial dimensions. The system may align the image data with an axis that passes through an apex and base of the left ventricle. The system may predict, based on a machine learning model and the imaging data, locations of a plurality of anchor points over a cardiac cycle. The system may output the predicted locations of the anchor points.

The invention discloses a myocardial activity concentration determination method and a related device, and relates to the technical field of nuclear medicine cardiac imaging, and the method comprises the following steps: converting acquired cardiac muscle body data under a human body coordinate system into cardiac muscle body data under a mandrel coordinate system; aiming at the cardiac muscle body data under the mandrel coordinate system, dividing the cardiac muscle body data under the mandrel coordinate system into ellipsoidal heart muscle body data and cylindrical heart muscle body data along the cardiac muscle short axis direction of the mandrel coordinate system; and respectively performing fan-shaped sampling and parallel sampling on the ellipsoid heart body data and the cylindrical heart body data to obtain multi-layer ellipsoid cardiac muscle short axis data and multi-layer cylindrical cardiac muscle short axis data. Carrying out data sampling on each layer of ellipsoid cardiac muscle short axis data and each layer of cylindrical cardiac muscle short axis data to obtain the cardiac muscle activity concentration of the left ventricle, the cardiac muscle activity concentration of the left atrium and the cardiac muscle activity concentration of the basal part; and more accurate myocardial activity concentration is determined based on comprehensive calculation of the myocardial activity concentration of the three regions obtained by data sampling.

A catheter-based ultrasound imaging system configured to provide a full circumferential 360-degree view around an intra-vascular / intra-cardiac imaging-catheter-head by generating a three-dimensional view of the tissue surrounding the imaging-head over time. The ultrasound imaging system can also provide tissue-state mapping capability. The evaluation of the vasculature and tissue characteristics include path and depth of lesions during cardiac-interventions such as ablation. The ultrasound imaging system comprises a catheter with a static or rotating sensor array tip supporting continuous circumferential rotation around its axis, connected to an ultrasound module and respective processing machinery allowing ultrafast imaging and a rotary motor that translates radial movements around a longitudinal catheter axis through a rotary torque transmitting part to rotate the sensor array-tip. This allows the capture and reconstruction of information of the vasculature including tissue structure around the catheter tip for generation of the three-dimensional view over time.

This invention provides a method for refining a surface mesh for mapping cardiac chambers. The method includes obtaining a surface mesh mapping cardiac chamber anatomy, wherein the mapped surface mesh includes a central region representing the cardiac chamber and an outer region representing peripheral cardiac structures connected to the cardiac chamber, and wherein the mapped surface mesh includes a first view of anatomical landmarks within the cardiac chamber, and image data of the cardiac chamber anatomy of the object is obtained. The central region of the mapped surface mesh is deformed based on a first segmentation algorithm configured according to one or more predetermined shape constraints, and the outer region of the mapped surface mesh is deformed based on a second segmentation algorithm configured according to the image data, thereby producing a deformed outer region. The deformed central region and the deformed outer region are then combined to generate a refined mapped surface mesh.