6944results about "Sonic diagnostics" patented technology

An image processing apparatus is disclosed. The image processing apparatus of the present invention comprises: an image receiving unit for receiving a first image and a second image of the same object taken at different times; a processor for obtaining transformation information by registering the first image on the basis of the second image, obtaining a first segment image corresponding to an area of the object from the first image, and generating a second segment image corresponding to an area of the object of the second image by transforming the obtained first segment image according to the transformation information; and an output unit for outputting the second segment image.

The invention discloses an intelligent planning method for a personalized scanning path of an ultrasonic robot, and relates to the field of ultrasonic robos.The intelligent planning method comprises the steps that anatomical structure information and clinical scanning demand information of a to-be-scanned part of a target patient are collected, a patient exclusive basic information set is established, and the anatomical structure information comprises spatial distribution characteristics of all tissues of the part; clinical demand information comprises a preset focus region and a scanning precision index, an exclusive basic information set is established by collecting an anatomical structure of a to-be-scanned part of a patient and the clinical scanning demand information, spatial correlation characteristics are analyzed, and a real-time physiological and anatomical position dynamic correlation rule is embedded to construct a dynamic anatomical correlation model; and individual anatomical dynamic changes of the patient can be accurately matched.

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and / or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and / or dynamically identify one or more features, such as plaque and vessels, and / or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, perform computational fluid dynamics analysis, facilitate assessment of risk of heart disease and coronary artery disease, enhance drug development, determine a CAD risk factor goal, provide atherosclerosis and vascular morphology characterization, and determine indication of myocardial risk, and / or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and / or quantified parameters.

The invention relates to the technical field of ultrasonic detection, and discloses an ultrasonic scanning path optimization and three-dimensional reconstruction method, device, equipment and medium, and the method comprises the steps: positioning a key mark point of a target area, generating an initial scanning path, and controlling an ultrasonic probe to move along the initial scanning path to collect first ultrasonic image data, extracting target structure features to construct an initial three-dimensional point cloud model; establishing a surface projection model; fitting to generate a surface profile curve and calculating the tangential direction of a sampling point; optimizing the orientation of an ultrasonic probe based on the tangential direction to generate an optimized scanning path; and reconstructing a final three-dimensional model. According to the invention, through key mark point positioning and incident direction optimization based on the tangential direction, the scanning path of the probe is enabled to be adaptive to curvature change of the target area, and through combination of real-time contact force adjustment and multi-stage image data acquisition, three-dimensional point cloud space coverage and imaging consistency are improved, and high-precision three-dimensional reconstruction of a complex anatomical structure is realized.

The invention relates to the technical field of robot control, and discloses a robot scanning path adjusting method, device, equipment and medium, and the method comprises the steps: controlling a robot equipped with a sensor to move along a preliminary path, collecting a preliminary two-dimensional image of a target object, processing the image, extracting the feature points of the target object, and combining the spatial information of the sensor when the image is collected; the method comprises the steps of generating a primary three-dimensional point cloud, determining a plurality of ideal sensor postures based on the primary three-dimensional point cloud, determining a new sensor position of each posture on a contactable surface to generate a re-planned scanning path, controlling a robot to move along the re-planned scanning path, adjusting the sensor postures, and collecting a final two-dimensional image of a target object. According to the method, the scanning path is optimized in combination with the initial three-dimensional point cloud local surface normal direction, so that the attitude of the sensor is matched with the geometrical characteristics of the target surface, the problem of three-dimensional reconstruction surface breakage caused by inter-frame pose mismatching under free breathing is solved, and the accuracy of autonomous ultrasonic scanning of the robot is improved.

The invention discloses a lower limb muscle fatigue assessment method and system based on multi-modal physiological signals, and relates to the technical field of biomedical engineering, target muscles are selected, sEMG signals, AUS signals and respiratory flux VE data are synchronously collected, and RPE is recorded; preprocessing various signals to remove interference and abnormal points; extracting sEMG time-frequency domain features and AUS muscle thickness features; fusing features and constructing vectors in a standardized manner; dividing five fatigue grades; and a data set is divided according to stratified sampling, a model is optimized through five-fold cross validation, and real-time features are input to output a fatigue level. Multi-modal physiological signals are fused, fatigue evaluation accuracy is improved, different fatigue stages are finely adapted, muscle load and energy consumption are reduced through personalized adaption and a dynamic adjustment strategy, rehabilitation training safety and comfort are improved, and efficient recovery of lower limb movement functions is assisted.

The invention discloses a hypertensive heart disease early screening system fusing ultrasonic multiple parameters, which comprises the following steps: acquiring ultrasonic image data and physiological index monitoring parameters of a patient at different time points, performing difference comparison on heart structure parameters to generate time sequence change data, and establishing a multi-dimensional data fusion scheme based on the time sequence change data and physiological indexes; according to the fusion scheme, acute risk trigger factors are identified, blood flow abnormal parameters are generated, and emergency threshold comparison is carried out to generate acute risk early warning signals; extracting a myocardial strain degradation rate to determine a chronic degradation acceleration time point, carrying out disease progress stage association to generate a chronic risk layering curve, and establishing a clinical index comparison table; carrying out double-layer correlation on the acute risk early warning signal and the chronic risk layering curve, and carrying out calibration judgment to generate a comprehensive risk judgment sequence; the sequence is decomposed into an acute judgment layer and a chronic judgment layer, a risk threshold value is configured to generate an instant early warning signal, a layered screening report is formed, and technical support is provided for early discovery of the hypertensive heart disease.

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and / or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and / or dynamically identify one or more features, such as plaque and vessels, and / or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and / or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and / or quantified parameters.

A method for locating an unknown arrangement of ultrasound transducer elements includes acquiring a set of raw ultrasound data using a flexible or rigid array of transducer elements, extracting a set of features from the ultrasound data, the features being derived from fundamental physics of ultrasound propagation and structural characteristics of a target object being imaged, organizing and structuring the extracted features as input for a machine learning model, and determining spatial coordinates of each ultrasound transducer element based on an output of the machine learning model.

According to embodiments, a system for imaging a blood flow in a region of interest of a patient includes: a display configured to display an image; a processor configured to execute the instructions to: obtain ultrasound imaging data based on an imaging signal; select the region of interest in the ultrasound image data; determine at least one characteristic of a blood flow in the region of interest; generate an animation indicating the at least one characteristic of the blood flow in the region of interest, wherein the animation indicates the blood flow during a single time slot; and control the display to display a static image including the region of interest and the animation within the region of interest.

The invention discloses a remote ultrasonic probe attitude synchronization and closed-loop control method based on inertial navigation, which integrates an inertial sensor technology, an attitude resolving algorithm, a three-dimensional visual interaction interface and a multi-mode control mechanism, and aims to realize accurate operation synchronization between a remote ultrasonic expert and a local ultrasonic inspection object. Therefore, the accuracy, the stability and the usability of remote ultrasonic examination are improved, the dependence on the skill level of a local operator is reduced, and the service range and the clinical efficiency of ultrasonic experts are expanded.

An intracardiac echocardiography (“ICE”) catheter handle, including a housing having a longitudinal axis, the housing having a proximal end and a distal end. A first actuator can be positioned on a first portion of the housing in a plane aligned with the longitudinal axis, the first actuator coupled to a first controller, the first actuator and first controller configured to control a catheter coupled to the first controller in a first direction and a second direction in the first plane. A second actuator can be positioned on a second portion of the housing in a second plane aligned with the longitudinal axis, the second actuator coupled to a second controller, the second actuator and second controller configured to control a catheter coupled to the second controller in a third direction and a fourth direction in the second plane, wherein first plane is aligned orthogonally to the second plane.

An ultrasound-imaging system includes an ultrasound probe coupled with a console. Operations of the system can include detecting one or more blood vessels within the ultrasound image and identifying each blood vessel as a vein, an artery or other anatomic element using doppler ultrasound functionality of the ultrasound probe. Operations can also include determining a confidence for the blood vessel identification and defining a window for doppler ultrasound operation. Operations can further include assessing a blood flow rate within blood vessels, and superimposing notifications atop the ultrasound image pertaining to the identity of the blood vessel including a confidence for the identity.

The invention discloses a cerebral vessel anomaly analysis method based on a transcranial Doppler ultrasound image, which comprises the steps of TCD image data acquisition, TCD image space-time filtering preprocessing, automatic blood vessel positioning and three-dimensional modeling, the method comprises the steps of generating a standardized blood vessel segmentation model and a static blood vessel network graph, extracting blood flow quantitative parameters and spectrum qualitative features, analyzing multi-blood vessel space correlation features through a graph attention network, performing primary classification on blood flow states, performing secondary classification on lesion types, making risk grading judgment, generating intervention suggestions and outputting a structured report. By setting an automatic parameter measurement method, the manual operation time of doctors is shortened, and the speed and accuracy of lesion judgment are improved through automatic standardization judgment of frequency spectrum forms and association of multi-dimensional parameters. Meanwhile, the experience requirement of doctors for judging the lesion is reduced, and reference is conveniently provided for batch screening of primary hospitals.

The invention relates to the technical field of medical treatment, in particular to ultrasonic equipment and an image processing method. In the embodiment of the invention, an ultrasonic image of a detection part is generated according to an ultrasonic echo signal which is received by an ultrasonic probe and is reflected by the detection part; feature extraction is carried out on the ultrasonic images through encoders in multiple layers of segmentation units contained in the segmentation network; processing the multiple groups of target object structure features output by the encoder in the multi-layer segmentation unit through the decoder in the multi-layer segmentation unit to obtain a segmentation result of the target object structure in the ultrasonic image; and performing partition processing on the ultrasonic image according to a segmentation result, and performing fuzzy enhancement processing on a partition critical region to obtain a processed ultrasonic image.

A method and corresponding system of identifying coronary artery disease. The method comprises receiving contrast cardiac CT data indicative of a contrast cardiac CT scan carried out on a patient, and analysing the contrast cardiac CT data using machine learning to identify a plurality of seed points in the contrast cardiac CT data expected to correspond to locations in cardiac arteries of the patient. The method also comprises producing data indicative of transverse image slices of the cardiac arteries of the patient using the contrast cardiac CT data and the identified seed points, analysing the transverse image slice data using machine learning to produce inner artery wall data and outer artery wall data indicative of predicted respective inner and outer walls of the coronary arteries of the patient, and identifying presence of coronary artery disease using the predicted inner and / or outer walls of the coronary arteries of the patient.

The invention provides a heart valve regurgitation detection method and system and a medium. The method comprises the steps that regurgitation area identification caused by heart valve structure or function abnormity is obtained; performing principal component analysis on the regurgitation area, and determining the main extension direction of the regurgitation of the corresponding heart valve; determining at least one morphological characteristic parameter of the reflux region according to the main extension direction; and determining the regurgitation state information of the heart valve according to the morphological characteristic parameters. According to the method, the spatial distribution of a reflux region is subjected to characteristic decomposition through principal component analysis, a complex irregular blood flow form is converted into a main extension direction with definite physical significance, and form characteristic parameters are calculated based on the main extension direction; random errors caused by subjective view angle differences or insufficient experience when valve reflux parameters are manually measured can be eliminated, and valve reflux evaluation results obtained by different operators under different detection conditions have high consistency and repeatability.

The invention relates to the technical field of medical instruments, and discloses a breast cancer sentinel lymph node positioning system and method, and the system comprises a data collection subsystem, a space positioning subsystem and a central processing subsystem. The method comprises the following steps: acquiring an anatomical structure image, a radioactivity counting rate and fluorescence intensity after performing primary fluorescence, radioactivity and secondary pulse type fluorescence tracer injection in sequence; establishing a global coordinate system and generating an anatomical region of interest; constructing a weighted directed topological graph based on the initial fluorescence data, and obtaining a baseline flow velocity; extracting radionuclide dynamic characteristics based on the radioactive data; a functional flow rate attenuation coefficient is calculated based on the second pulsed fluorescence data. And a multi-factor scoring model is applied, topological information, dynamic characteristics and functional flow velocity attenuation coefficients are fused, and a comprehensive score is calculated to identify the sentinel lymph node. According to the method, the lymphatic flow topological structure, nuclide dynamics and functional flow velocity information are combined, and the positioning accuracy and reliability are improved.

The invention discloses a self-adaptive fitting ultrasonic probe flexible accessory which comprises a flexible cover sleeve body, and the flexible cover sleeve body is made of a medical-grade elastic material and is provided with a containing cavity matched with an ultrasonic probe in shape; the sealing opening is formed in the bottom of the flexible cover sleeve body and is used for tightly wrapping the emitting surface of the probe; the liquid storage cavity is a closed cavity and is pre-filled with a high-viscosity medical ultrasonic coupling agent; the self-adaptive attaching layer is composed of the bottom wall of the flexible cover sleeve body. Wherein the liquid storage cavity is located between the sealed opening and the self-adaptive attaching layer, and the coupling agent is evenly distributed on the contact interface of the probe and the skin under the action of pressure; the probe is matched with a common ultrasonic probe, and the imaging effect of the probe in an uneven body surface area is improved on the premise that the main body structure of the probe is not changed.

A method of diagnosing a condition of bodily tissue using a computer, the method comprising comparing, using a computer, a 3D tissue model derived from an ultrasound scan of the bodily tissue with at least one 3D tissue model having common tissue with the bodily tissue, and diagnosing a condition of the bodily tissue responsive to comparing the 3D tissue models.

The invention provides an ultrasonic control method for real-time scanning quality and self-adaptive acquisition and related equipment, and the method comprises the steps: synchronously acquiring an ultrasonic signal and at least one additional sensor signal in an acquisition period of scanning equipment; calculating multi-dimensional quality indexes including a signal quality index, an operation stability index and a contact state index in real time based on the ultrasonic signal and the additional sensor signal, and generating an overall quality score according to the multi-dimensional quality indexes; judging whether the total quality score reaches a preset qualified threshold value or not; if the total quality score is lower than a qualified threshold value, quality loss factors are determined according to the total quality score, control actions used for improving subsequent collection quality are generated and executed based on the quality loss factors, and the control actions comprise one or more of sending prompt information to an operator and automatically adjusting collection parameters of the scanning equipment. According to the invention, multi-dimensional evaluation and autonomous decision making are carried out on the ultrasonic quality by fusing additional sensor multi-mode signals, so that the ultrasonic acquisition quality is improved.

Disclosed is an intraluminal imaging system, including an intraluminal imaging catheter or guidewire configured to be positioned within an anatomy of a patient, and a processor circuit in communication with the imaging catheter or guidewire, wherein the processor circuit is configured to receive a plurality of cross-sectional images of the anatomy from the imaging catheter or guidewire. The processor is further configured to compute, using image processing of at least one of the cross-sectional images, a value of the anatomy, estimate a cross-sectional shape of the anatomy to be circular, calculate a diameter of the anatomy based on the computed value and the estimated circular shape, and output the diameter of the anatomy to a display.

The invention provides a tissue viscoelasticity calculation method and system based on wavelet transform, and the method comprises the steps: exciting and generating shear waves at a target region of a tissue, and extracting shear wave information; carrying out wavelet transformation on the shear wave information, and extracting frequency domain information in the shear wave information, so as to obtain time-frequency domain information of shear waves; taking any point on the transverse tangent plane as a target point, and performing cross-correlation between the time-frequency domain information of the target point and the time-frequency domain information of the other points by using a cross-correlation algorithm to obtain phase differences between the target point and the other points under different frequencies; determining phase velocities of shear waves under different frequencies according to phase differences between the time-frequency domain signals of the target point and the time-frequency domain signals of other points under different frequencies; and fitting the phase velocities of the shear waves under different frequencies to obtain a viscosity value and an elasticity value corresponding to the target area of the tissue. The method does not need to collect data for many times, reduces errors caused by data collection, and improves the mechanical characteristic calculation precision of the tissue.

The invention relates to the technical field of medical equipment, in particular to a multi-modal respiratory signal acquisition system for realizing appearance and data dual individuation for multi-body-type respiratory patient crowds, which can generate an individualized patient respiratory data set through wearable waistcoat design and respiratory data weight calibration. The system mainly comprises a waistcoat body, an acquisition module, a communication module, a storage module and a personalized weight software module. The acquisition module comprises A-type ultrasound, an electroencephalogram sensor, a myoelectricity sensor, an inertial sensor, a flow meter and a body surface tension band. In the collecting process, firstly, a patient wears a waistcoat, the length of a bandage is adjusted, sensor collecting point positions are adjusted to medical reference positions, and then the sensors are synchronously triggered through the communication module to conduct real-time data collection. And a personalized weight software module is used for generating weight calibration for validity and significance of each modal data according to the basic medical record of the patient, and finally, the data and the weight are jointly stored in a storage module. According to the invention, the comprehensiveness and precision of data can be improved, and patient personalized acquisition which is widely applicable is realized.

The invention discloses a stomach tube tail end three-dimensional positioning method based on a high-precision permanent magnet mark and a flexible TMR array. The method comprises the following steps: disinfecting a stomach tube and a permanent magnet marker; the miniaturized permanent magnet marker is firmly installed at the front end of the stomach tube; reserving a mounting position at the front end of the stomach tube, and inserting the stomach tube into the esophagus of a patient through a nasal cavity or an oral cavity until the stomach tube reaches a preset position; flexible TMR sensor arrays in double-sided distribution are arranged in the chest area and the back area of the patient; according to magnetic field data detected by a TMR sensor array, coordinates of a permanent magnet marker in a sensor coordinate system are solved through magnetic dipole modeling and nonlinear optimization, a thoracic coordinate system transformation matrix is established, and three-dimensional position coordinates of the permanent magnet marker in a world coordinate system are determined; a magnetic dipole reverse solution positioning method is adopted, and meanwhile, the zero radiation exposure risk is ensured; spatial registration with an ultrasonic image is supported, and the positioning precision and the anti-interference capability are improved.

The invention is suitable for the technical field of ultrasonic imaging, and provides a three-dimensional ultrasonic imaging method and system, computer equipment and a computer program product, and the method comprises the steps: transmitting a multi-angle composite plane wave sequence to a target region through a one-dimensional ultrasonic array with the frequency gradual change characteristic in the elevation direction, and receiving a reflected echo signal sequence, generating a target gray-scale image sequence corresponding to the echo signal sequence, acquiring coordinates of each ultrasonic contrast agent microbubble in each frame of gray-scale image, generating a two-dimensional coordinate set, calculating the axial half-peak full width of a point spread function region of each ultrasonic contrast agent microbubble, and calculating the axial half-peak full width of the point spread function region of each ultrasonic contrast agent microbubble; determining the coordinate of each ultrasonic contrast agent microbubble in the elevation angle direction based on the axial half-peak full width, generating an elevation angle coordinate set, and generating a three-dimensional contrast image of the target area based on the two-dimensional coordinate set and the elevation angle coordinate set. According to the method provided by the invention, the problem that three-dimensional ultrasonic imaging is limited by the surface ultrasonic array can be solved, and low-cost, simple and efficient three-dimensional ultrasonic imaging based on the one-dimensional ultrasonic array is realized.

The invention relates to a method for determining the speed of sound in a fluid in the region of an implanted, vascular support system, comprising the following steps: a) sending an ultrasonic signal by means of an ultrasonic sensor b) reflecting the ultrasonic signal on at least one sound reflector, which is visible in the field of vision of the ultrasonic sensor and arranged at a defined distance at least to the ultrasonic sensor or to a further sound reflector, c) receiving the reflected ultrasonic signal, d) determining the speed of sound in the fluid using the reflected ultrasonic signal.

A real-time artificial intelligence (AI) framework is provided for the automated analysis of radiological images and detection of disease, such as extracapsular extension (ECE) in prostate cancer. The system includes a dual deep learning architecture comprising a first convolutional neural network (CNN) for identifying diagnostically relevant image slices from three-dimensional MRI data, and a second CNN for classifying disease presence based on those slices. A preprocessing pipeline standardizes and harmonizes image input, and cropping algorithms isolate the region of interest for enhanced model performance. This framework enables scalable, high-accuracy diagnosis across various imaging modalities including but not limited to MRI, CT, PET, ultrasound, and diverse disease types, improving clinical decision-making and supporting integration into real-time radiology workflows.

The invention relates to the technical field of ultrasonic detection, and discloses a robot ultrasonic detection method, device and equipment based on three-dimensional perception and a medium, and the method comprises the steps: obtaining three-dimensional point cloud data of the surface of a target object; generating a scanning path for detecting the target object based on the three-dimensional point cloud data; controlling a motion execution device to drive the detection probe to move along the scanning path to obtain ultrasonic image data of the internal structure of the target object; in the moving process of the detection probe, the contact force between the detection probe and the target object is maintained within a preset force value range; analyzing the ultrasonic image data, identifying a lumen contour and determining a narrowest position point; and adjusting the posture of the detection probe at the narrowest position point and executing secondary detection to obtain hydrodynamic data. The self-adaptive scanning path is generated through the three-dimensional point cloud data, the movement and the contact force of the detection probe are controlled, the ultrasonic image and the space position are associated, and the problems that the detection path is not attached to the curved surface, the contact force fluctuates, and the image space is not synchronous are solved.

Methods and systems for identifying a region of interest in breast tissue utilize artificial intelligence to confirm that a target lesion identified during imaging the breast tissue using a first imaging modality (e.g. x-ray imaging) has been identified using a second imaging modality (e.g. ultrasound imaging). A computing system operating a lesion matching engine utilizes a machine learning classifier algorithm trained on cases of x-ray images and corresponding ultrasound images in which lesions were identified for further analysis. The lesion matching engine analyzes a target lesion identified with x-ray imaging and a potential lesion identified with ultrasound imaging to determine a likelihood that the target lesion is the same as the potential lesion. A confidence level indicator for the lesion match is presented on a display of a computing device to aid a healthcare provider in locating a lesion in breast tissue.