8000results about "Radiation diagnostics" patented technology

In a measurement processing apparatus for measuring a geometric feature of an object image: a measurement-reference-element setting unit automatically sets at least one first measurement reference element for use in measurement of the geometric feature of the object image, at at least one first position on the object image based on first image data representing the object image and position information indicating at least one second position of at least one second measurement reference element which is set on a measurement reference image corresponding to the object image; and a geometric-feature measurement unit measures the geometric feature of the object image based on the at least one first position of the at least one first measurement reference element.

The invention discloses a cerebral apoplexy risk prediction method and system based on multi-modal data fusion. The method comprises the following steps: A1, a data acquisition and preprocessing step; a2, a feature embedding and multi-modal fusion step; a3, a self-attention mechanism optimization feature fusion step; a4, a multi-mode cooperative training step; and A5, dynamic prediction and real-time updating. By integrating medical image data, gene data, electronic health record (EHR) and biomarker data, the risk of cerebral apoplexy can be comprehensively evaluated, and the limitation of a single data source is solved. According to the method, independent feature extraction and embedding processing are carried out on various data through a deep learning model, deep information in each data mode can be captured, and more detailed and accurate risk assessment is provided.

A computer-implemented method of providing a temporal sequence of 3D angiographic images (110) representing a flow of a contrast agent through a region of interest (120), is provided. The method includes: inputting (S130) volumetric image data (130a, 130b), and a temporal sequence of 2D angiographic images (140) into a neural network (NN1); and generating (S140) the predicted temporal sequence of 3D angiographic images (110) representing the flow of the contrast agent through the region of interest (120) in response to the inputting.

The invention relates to the technical field of image processing, and discloses an AR technology-based precise positioning method and system for minimally invasive surgery of hepatobiliary surgery. The method comprises the steps that blood vessel network data are extracted through a medical image sequence, a three-dimensional structure diagram is generated, operation target points are marked, and a coordinate system is established; collecting dynamic data for mapping matching, and establishing a real-time tracking model; constructing an augmented reality scene and implanting a navigation path; acquiring an instrument position calculation track, and comparing with a navigation map to generate an instruction; constructing a projection interface to display the key area; recording the whole process and evaluating the operation quality. By establishing the real-time tissue deformation tracking model, a multi-source data fusion accurate positioning mechanism and an intelligent operation quality evaluation system, the accuracy and reliability of operation navigation are effectively improved.

A method includes receiving data of a current state of a dental site of a patient, the data comprising a plurality of data items generated from a plurality of oral state capture modalities. The data is processed using a plurality of trained machine learning models that output estimations of one or more oral conditions. The data and / or estimations are processed to generate at least one of a) one or more actionable symptom recommendations for one or more oral health problems associated with the one or more oral conditions or b) one or more diagnoses of the one or more oral health problems. One or more treatment recommendations are generated for treatment of at least one oral health problem based on at least one of the one or more actionable symptom recommendations or the one or more diagnoses.

A histotripsy therapy system configured for the treatment of tissue is provided, which may include any number of features. Provided herein are systems and methods that provide efficacious non-invasive and minimally invasive therapeutic, diagnostic and research procedures. In particular, provided herein are optimized systems and methods that provide targeted, efficacious histotripsy in a variety of different regions and under a variety of different conditions without causing undesired tissue damage to intervening / non-target tissues or structures.

The present invention relates to image processing of angiograms. In order to provide improved angiograms, a device (10) for enhancing angiograms is provided. The device comprises a data input (12), a data processor (14) and an output interface (16). The data input is configured to provide at least one angiographic image showing a vascular structure of interest comprising a plurality of vessel branches. The data processor is configured to determine at least one branch of interest from the angiographic image. The data processor is configured to segment the angiographic image for identifying possible branches of the vascular structure. The data processor is configured to select branches based on the identified possible branches and the determined branch of interest. The data processor is configured to estimate attenuation values of the selected branches. The data processor is configured to subtract at least a predetermined part of the estimated attenuation values from the angiographic image to generate a corrected angiogram. The output interface is configured to provide the corrected angiogram.

The present disclosure relates to a method, performed by a processor, for processing a blood vessel image from a blood vessel image, the method comprising the steps of: extracting a target blood vessel from a blood vessel image; determining a region of interest (ROI) in an extraction result of the target blood vessel on the basis of a first input received from a user; and within the determined ROI, identifying an error portion in the extraction result on the basis of a second input received from the user, and correcting the identified error portion.

A method of visualizing structural information of pulmonary vessels in medical images includes obtaining structural information of pulmonary vessels based on anatomical structure features of the pulmonary vessels from a medical image based on segmentation results of a pulmonary vascular region of the medical image; obtaining pulmonary embolism finding information in the pulmonary vessels of the medical image; visualizing the structural information of the pulmonary vessels in accordance with hierarchical information; and visualizing the pulmonary embolism finding information in association with individual sub-regions of the structural information of the pulmonary vessels visualized in accordance with the hierarchical information.

A method for auxiliarily planning a fracture reduction path based on an augmented reality technology includes: obtaining fracture image data for a fracture area of a patient, the fracture image data including computer tomography (CT) data and X-ray data; reconstructing a three-dimensional model of a fracture part based on the fracture image data; matching and calibrating the three-dimensional model of the fracture part based on the fracture area of the patient in an actual scene; inputting a calibrated three-dimensional model of the fracture part and a corresponding fracture type and fracture surgery requirement into a fracture reduction path planning model to determine at least one corresponding optimized fracture reduction path, where the fracture reduction path planning model includes a cascaded reinforcement learning (RL) module and a multi-physics field simulation optimization module; and rendering each fracture reduction path, and determining a target fracture reduction path according to a detected interactive instruction.

A histotripsy therapy system configured for the treatment of tissue is provided, which may include any number of features. Provided herein are systems and methods that provide efficacious non-invasive and minimally invasive therapeutic, diagnostic and research procedures. In particular, provided herein are optimized systems and methods that provide targeted, efficacious histotripsy in a variety of different regions and under a variety of different conditions without causing undesired tissue damage to intervening / non-target tissues or structures.

The present disclosure provides a method and an apparatus for acquiring a contour line of a blood vessel according to a centerline of the blood vessel. The method comprises: extracting a centerline of a blood vessel according to a two-dimensional coronary artery angiogram image (S100); obtaining an image of a straightened blood vessel according to the centerline of the blood vessel (S200); setting a threshold Dthreshold for a diameter of the blood vessel on the image of the straightened blood vessel (S300); generating a preset contour line of the blood vessel on both sides of a centerline of the straightened blood vessel according to the Dthreshold (S400); making the preset contour line of the blood vessel step-by-step approach the centerline of the straightened blood vessel to acquire a contour line of the straightened blood vessel (S500); projecting the contour line of the straightened blood vessel back onto the image of the centerline of the blood vessel to obtain a contour line of the blood vessel (S600).

The invention provides an acute cerebral apoplexy early-stage intelligent screening and early warning method and system based on deep learning, and relates to the technical field of medical imaging and artificial intelligence, and the method comprises the steps: obtaining a multi-temporal angiography image of the brain of a patient through a pulse-type dynamic imaging scheme, extracting hemodynamic features through a double-flow feature extraction network, and obtaining a multi-temporal angiography image of the brain of the patient; and constructing a vasculopathy risk distribution diagram by combining a vascular structure analysis model, and marking a potential embolism risk area. Furthermore, in combination with tissue perfusion parameters obtained by multispectral imaging and brain tissue function parameters obtained by electroencephalogram signals, an ischemic penumbra region is identified by using a self-adaptive threshold segmentation model. And finally, based on the ischemic penumbra area, the tissue perfusion parameters and the brain tissue function parameters, calculating a risk level by using a hierarchical decision model with a space-time attention mechanism, and generating a corresponding clinical intervention scheme. According to the invention, the early accurate screening and risk early warning of acute cerebral apoplexy can be realized, and the clinical intervention efficiency is improved.

A system (100) for providing a normalised microcirculatory resistance value for a vessel (110), is provided. The system includes one or more processors (120) configured to: compute (S110) a microcirculatory resistance value for the vessel (110) based on a transit time (TT) taken for an injected bolus to travel between a proximal position (Posa) in the vessel, and a distal position (Posd) in the vessel; and divide (S120) the computed microcirculatory resistance value by a transit length (dT) representing a length of the vessel between the proximal position (Posa) and the distal position (Posd), to provide the normalised microcirculatory resistance value.

Provided is a method for computing a SYNTAX score using a cardio angiogram, which is performed by at least one processor of a computing device, and includes acquiring an angiogram of a cardiovascular system, providing a cardiovascular segment map associated with the angiogram, in response to a user input that selects one of one or more frames included in the acquired angiogram and associates the selected one frame with a cardiovascular segment included in the cardiovascular segment map, associating the selected one frame with the cardiovascular segment, generating, using the selected one frame, an analysis result for a lesion in the associated cardiovascular segment, determining, based on the analysis result, a SYNTAX score for at least a part of the cardiovascular system, and generating an indication of the SYNTAX score.

A measurement and imaging instrument capable of beamforming with high speed and high accuracy without approximate calculation. The instrument includes a reception unit which receives a wave arriving from a measurement object to generate a reception signal; and an instrument main body which performs a lateral modulation while superposing two waves in a two-dimensional case and three or four waves in a three-dimensional case in beamforming processing of the reception signal in which at least one wave arriving from the measurement object is processed as being transmitted or received in the axial direction or directions symmetric with respect to the axial direction to generate a multi-dimensional reception signal, performs Hilbert transform with respect to the multi-dimensional reception signal, and performs partial derivative processing or one-dimensional Fourier transform to generate analytic signals of the multi-dimensional reception signals of the two waves or the three or four waves.

The invention is a delivery catheter, e.g., a guide catheter, having an imaging element in proximity to the distal end of the catheter. Catheters of the invention are able to placement of the catheter in proximity to an ostium, thereby increasing the efficiency of contrast delivery while reducing the risk of ischemia due to blocked blood supply. The invention additionally assists in maintaining catheter position during delivery of a fluid from the catheter, resulting in better performance with less fluid. For example, a catheter of the invention can be used to produce improved fluoroscopic images with less overall contrast. This improvement reduces the risk of an allergic reaction to the contrast while decreasing the length of time for a procedure, i.e., because of a need to re-contrast.

The present disclosure provides a method for correcting a resting blood flow velocity on the basis of an interval time between angiogram images, comprising: acquiring, in an angiography state, an average blood flow velocity Vh from a coronary artery inlet to a distal end of a coronary artery stenosis (S100); acquiring a time difference Δt between start times of two adjacent bolus injections of contrast agent (S200); obtaining a correction coefficient K according to the time difference Δt (S300); obtaining a resting blood flow velocity Vj according to the correction coefficient K and the average blood flow velocity Vh (S400), as well as an apparatus configured for implementing the above method. The disclosure obtains the resting blood flow velocity Vj according to the correction coefficient K and the average blood flow velocity Vh.

Embodiments include methods of identifying a personalized cardiovascular device based on patient-specific geometrical information, the method comprising acquiring an anatomical model of at least part of the patient's vascular system; performing, using a processor, one or more of geometrical analysis, computational fluid dynamics analysis, and structural mechanics analysis on the anatomical model; and identifying, using the processor, a personalized cardiovascular device for the patient, based on results of one or more of the geometrical analysis, computational fluid dynamics analysis, and structural mechanics analysis of anatomical model.

Described herein is a platform and supported graphical user interface (GUI) decision-making tools for use by medical practitioners and / or their patients, e.g., to aide in the process of making decisions about a course of cancer treatment and / or to track treatment and / or the progress of a disease.

Described herein is a platform and supported graphical user interface (GUI) decision-making tools for use by medical practitioners and / or their patients, e.g., to aide in the process of making decisions about a course of cancer treatment and / or to track treatment and / or the progress of a disease.

A computer-implemented method for processing medical images may comprise: receiving image data for a patient; based on the received image data, determining: a patient-specific epicardial adipose tissue (EAT) metric or a patient-specific pericoronary adipose tissue (PCAT) metric, and at least one other patient-specific metric, and using the EAT metric or the PCAT metric, and the at least one other patient-specific metric, to determine a risk score for the patient or to classify a disease state of the patient.

Computer-implemented methods and systems are provided for quantitative hemodynamic flow analysis, which involves retrieving patient specific image data. A 3D reconstruction of a vessel of interest can be created from the patient specific image data. Geometric information can be extracted from the 3D reconstruction. A lesion position can be determined. Patient specific data can be obtained. Hemodynamic results can be calculated based on the geometric information, the lesion position and the patient specific data.

An infusion system may include a radioisotope generator that generates a radioactive eluate via elution, a beta detector, a gamma detector, and a controller. The beta detector and the gamma detector may be positioned to measure beta emissions and gamma emissions, respectively, emitted from the radioactive eluate. In some examples, the controller is configured to calibrate the infusion system using the gamma detector. For example, the controller may generate a radioactive eluate and measure the activity of the radioactive eluate using both the beta detector and the gamma detector. The high accuracy of the activity measured by the gamma detector may be used to calibrate the infusion system. In subsequent use, the infusion system calibrated using the gamma detector may adjust measurements made to monitor and / or control patient infusion procedures.

A method includes accessing a computerized tomography (CT) scan of a human subject and defining a first two-dimensional (2D) slice (200) of the scan and a second 2D slice (204) of the scan, so that the first and the second slices intersect in an intersection line (224) defining a desired trajectory. The method further includes overlaying on the intersection line an icon (250) representing an object used in a procedure on the human subject, and rendering a three-dimensional (3D) image (650) of the human subject, incorporating the overlayed icon, from the CT scan.

The invention relates to the technical field of medical image processing, in particular to an artificial intelligence assisted intraoperative imaging method, which comprises the following steps: S1, preprocessing a multi-modal medical image, segmenting and recognizing an anatomical structure by a deep learning model according to the preprocessed image, measuring anatomical parameters based on a segmentation and recognition result, and generating an operation planning path by artificial intelligence according to the anatomical parameters; s2, collecting a C-shaped arm perspective image stream in real time, dynamically tracking space coordinates of a surgical instrument, comparing the position of the instrument with a surgical planned path, calculating offset, and when the offset is greater than an offset threshold, outputting correction guidance through an AR superposition layer; and S3, monitoring an image quality index in real time, dynamically adjusting exposure parameters through a reinforcement learning model, and when a metal implant is detected, switching a dual-energy-spectrum mode and executing an artifact suppression algorithm. According to the method, preoperative precise planning and intraoperative assistance are realized through artificial intelligence, the problems of poor image quality and high radiation risk are solved through technical optimization, and the method has important clinical application value.

A method and apparatus for analyzing diagnostic image data are provided in which a plurality of acquisition images of a vessel of interest having been acquired with a pre-defined acquisition method is received at a trained classifying device and classified, by the classifying device, to extract at least one quantitative feature of the vessel of interest from at least one acquisition image of the plurality of acquisition images. The at least one quantitative feature is then output associated with the at least one acquisition image while the acquisition of the diagnostic image data is still in progress and one or more adjustable image acquisition settings are adjusted based on the at least one quantitative feature to optimize the acquisition of the diagnostic image data.

There is provided a method and a system for generating a 3D parametric mesh of an anatomical structure of a patient for storing multi-domain data therein. A plurality of anatomical segments having been obtained from segmentation of a set of images of a patient are received. A 3D mesh comprising a plurality of concentric 3D mesh layers is received, where each concentric 3D mesh layer includes a same predetermined number of nodes. A set of nodes in the 3D mesh corresponding to a respective anatomical segment is determined to obtain a respective correspondence rule therebetween. The set of nodes is encoded with a set of features from the respective anatomical segment by using the correspondence rule to obtain a 3D parametric mesh, each node of the set of nodes in the 3D parametric mesh being associated with a respective plurality of feature channels comprises the set of features.

To provide an image processing device capable of applying image processing to a moving image suitably in real-time even immediately after photography.SOLUTION: An image processing device for applying image processing to a moving image containing multiple frames of radiographic images, comprises: a selection unit that selects a learned model to be used for image processing of the frame being the processing target from among the multiple learned models with mutually-different input frame numbers according to the acquired frame numbers; and an inference processing unit that performs inference processing using the selected learned model in the image processing of the frame being the processing target.SELECTED DRAWING: Figure 7

A single vertebra segmentation method, device, equipment and storage medium. The method comprises: acquiring first spine boundary information, which is boundary information of a spine in a segmentation result obtained through image segmentation of a raw CT image; acquiring first vertebra position information, which is information on the position of a single vertebra in the spine in the raw CT image; acquiring an initial image of the single vertebra according to the first spine boundary information and the first vertebra position information; marking the position of the single vertebra in the initial image of the single vertebra to generate an updated image of the single vertebra; and determining the single vertebra in a restored image corresponding to the raw CT image according to the updated image of the single vertebra. According to the present application, the spine in the CT image can be segmented on a single segment basis.