5583results 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.

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 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 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.

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.

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.

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.

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.

A computer implemented method for training a whole medical image foundation model, including: receiving a plurality of medical image datasets; extracting local sections of image data from the plurality of medical image datasets; obtaining one or more causal variables associated with the local sections and / or patient; training one or more self-supervised learning models based on the local sections of image data and the causal variables; combining the one or more trained self-supervised learning models with a deep learning network configured to combine a latent representation of the local sections of image data from the one or more trained self-supervised learning models into a patient-level representation; and combining, with the one or more trained self-supervised learning models and the deep learning network, at least one further network or function configured to accept the patient-level representation as input, the at least one further network or function operable to perform one or more patient-specific prediction tasks.

The invention belongs to the technical field of medical image assistance, and particularly relates to an auxiliary stereo imaging system and method for a complex chest trauma operation. By integrating multi-modal image data, real-time three-dimensional space capture, dynamic correction and risk score driven view adjustment, accurate assistance of the thymotomy operation process is achieved, the accuracy and safety of the operation are improved, the operation risk and operation difficulty are remarkably reduced, and the operation efficiency is improved. By acquiring and processing multi-modal image data in real time, a high-precision three-dimensional anatomical structure model containing thymus tissues, a blood vessel network and nerve distribution can be constructed, a visual surgical navigation view is provided for a doctor, meanwhile, a dynamic correction technology is adopted, thymus displacement parameters caused by thoracic cavity respiratory movement of a patient are monitored in real time, and the thoracic cavity of the patient can be accurately and accurately positioned. And on the basis, the real-time three-dimensional space data is dynamically adjusted, so that the spatial synchronization of the image data and the anatomical structure is ensured, and the navigation error caused by respiratory movement is effectively avoided.

An angiography image and intravascular image registration interaction method and apparatus, a device, and a medium. The method comprises: in an angiography image area on a registration interaction interface, displaying angiography image data of a target blood vessel (S110), wherein the angiography image data at least comprises a first index identifier marking an index position of the target blood vessel; in an intravascular image area on the registration interaction interface, displaying intravascular image data of the target blood vessel (S120), wherein the intravascular image data at least may comprise a second index identifier marking the index position; and in response to a movement operation for the displayed first index identifier or second index identifier, displaying the moved first index identifier in the angiography image area and displaying the moved second index identifier in the intravascular image area (S130).

An electronic device is disclosed. The electronic device comprises an image acquisition unit configured to acquire medical images captured at a plurality of positions, and a processor configured to generate tree structure data of three-dimensional candidate points corresponding to points along center lines of blood vessel regions of a reference image and a sub-image of the medical images, determine a three-dimensional path based on the tree structure data, determine a three-dimensional diameter for each of the points on the three-dimensional path, and reconstruct the three-dimensional shape of the blood vessels corresponding to the three-dimensional path based on the determined three-dimensional diameter.

A medical image processing device of an embodiment includes first and second image acquirers, a generator, and a calculator. The first image acquirer acquires a first fluoroscopic image of a patient. The second image acquirer acquires a second fluoroscopic image according to radiation of the patient at a time point different from that of acquisition of the first image using a detector. The generator generates a reconstructed image by reproducing the second image from the first image virtually arranged in a three-dimensional space on the basis of a position of the detector in the three-dimensional space. The calculator obtains a suitable position on the first image in the three-dimensional space on the basis of a degree of similarity between the second image and the reconstructed image. The generator generates the reconstructed image for use in the calculator and has a range larger than a range corresponding to the second image.

Method and systems are provided for characterizing blood flow in an atrioventricular valve of the human heart, the atrioventricular valve connecting an atrium with a corresponding ventricle of the heart, the ventricle being fluidly coupled to a particular vessel that transports blood outside the ventricle blood, which involve obtaining image data of the heart and identifying contours of the atrium and a region within the particular vessel within the image data. A time-density curve for the atrium can be calculated from the contour of the atrium and densitometric image data derived from the image data. A time-density curve for the region of the particular vessel can be calculated from the contour of the vessel region and the densitometric image data. Data that characterizes at least one regurgitation fraction related to the atrioventricular valve can be calculated from such time-density curves.

Provided are a data processing method and apparatus, a computing device, and a storage medium. The method may comprise: acquiring image data related to a target human body area; obtaining at least one predicted value of fractional flow reserve (FFR) of the target human body area on the basis of the image data; obtaining at least one confidence coefficient corresponding to the at least one predicted value; and displaying the at least one predicted value and the corresponding at least one confidence coefficient in an associated manner.

An electronic device for processing a blood vessel image according to an embodiment may include: an arc-shaped C-arm open toward the isocenter; a radiation source connected to the C-arm and emitting radiation to a target blood vessel located on a table; and a processor for computing a target distance from the radiation source to the target blood vessel, on the basis of a first vertical distance from the isocenter to the table and a second vertical distance from the target blood vessel to the table, and computing a physical distance of the target blood vessel by using the computed target distance, from a blood vessel image obtained using radiation.

Techniques for adjusting or editing respective segments of a contour of a given lumen segmentation of a portion of coronary arteries are described. The respective segments of the contour are adjusted by processing multiple cardiac images. Each of the multiple cardiac images depicts a portion of coronary arteries, i.e., the same portion of coronary arteries, within an anatomical region of interest. Respective magnitudes of one or more local segmentation uncertainties are determined based on the multiple cardiac images. Each of the one or more local segmentation uncertainties is associated with a respective segment of the contour of the given lumen segmentation. The respective segments of the contour are adjusted edited or manipulated based on the respective magnitudes of the one or more local segmentation uncertainties.

Methods and system for atrial fibrillation ablations and other cardiac procedures utilizes a cardiac mapping system for navigation and guidance, and includes an additional virtual reality (VR) system and an augmented reality (AR) or mixed reality (MR) system. The Cardiac mapping system utilizes medical images and patient's electrical signals. The virtual reality (VR) system is utilized pre-procedure for visualization and pre-procedure planning. The augmented reality (AR) or mixed reality (MR) system is utilized pre-procedure or intra-procedure. Methods and system are disclosed utilizing pre-built virtual device models which interact with 3D volume rendered structures from patient's CT or MRI of the region of interest (ROI) for the different type of cardiac procedure. With virtual reality (VR) the operator utilizes hand-held sensors. With augmented reality (AR) or mixed reality (MR) a combination of hand gestures and an X-box controller is used to manipulate virtual devices, anatomical structures in the Hologram.

Techniques for processing multiple cardiac images are disclosed. The multiple cardiac images, each of which depicts a portion of coronary arteries, i.e., the same portion of coronary arteries, within an anatomical region of interest, are obtained either during or after an angiography exam. A respective set of lumen radius measurements is determined based on each of the multiple cardiac images and comprises multiple lumen radius measurements respectively associated with multiple locations of the portion of the coronary arteries. A maximum stenosis severity profile and a minimum stenosis severity profile associated with the portion of the coronary arteries are respectively determined based on the respective sets of lumen radius measurements. A lumen radius profile associated with the portion of the coronary arteries is determined based on the maximum stenosis severity profile and the minimum stenosis severity profile. A respective value for each of at least one hemodynamic index at a given location of the portion of the coronary arteries is determined based on the lumen radius profile.

Dual-energy imaging of a recording region is provided by a recording arrangement with an X-ray tube assembly and an X-ray detector for receiving X-rays of an X-ray field emitted by the X-ray tube assembly in cone beam geometry. The field has a central beam, and the recording arrangement is rotated around the recording region for recording projection data of different directions of projection for two different X-ray spectra. For each X-ray spectrum, a three-dimensional image dataset of the recording region is reconstructed from the respective projection data. The projection data of the two X-ray spectra is recorded during the rotation that covers at least 360°. For each X-ray spectrum, an associated portion of the X-ray field is fixed over the rotation, and a corresponding, associated, fixed portion of the X-ray detector is used.

An apparatus for synchronizing a three-dimensional model of a patient's coronary arteries with an orientation of a medical imaging device is disclosed. In an example, an apparatus is configured to receive an indication that a three-dimensional model has been rotated. The indication includes a number of degrees of rotation of the three-dimensional model along a roll and / or pitch axis. The processor uses a correlation or transfer function to determine a rotational angulation position of the medical imaging device based on the number of degrees of rotation of the three-dimensional model along the roll and / or pitch axis. The processor transmits a command or instruction to the medical imaging device that is indicative of the desired rotational angulation position, thereby causing the medical imaging device to rotate to the desired position.

An electronic device according to one embodiment can acquire a first trendline related to vessels from a medical image; determine lesion candidates among the vessels on the basis of the first trendline; acquire a second trendline on the basis of a reference point selected in the vicinity of the lesion candidates; and determine a lesion site among the lesion candidates on the basis of the acquired second trendline.

A suspended travelling device and a medical imaging system. The suspended travelling device includes at least one rail, at least one guide belt, and a movable mechanism. The at least one guide belt is arranged on each rail along an extension direction of each rail. The movable mechanism has at least one first travel roller. Each first travel roller is rollable on and abuts against a surface of a corresponding guide belt, and a difference between material hardness of an outer peripheral surface of each first travel roller and material hardness of the corresponding guide belt is less than or equal to a preset material hardness threshold.

A method and apparatus for calculating the blood flow rate in a coronary artery, an electronic device and a storage medium. The method for calculating the blood flow rate in a coronary artery comprises the following steps: S1, acquiring an angiography image of the coronary artery, segmenting the angiography image of the coronary artery by using deep learning, and obtaining segmented images of a main vessel (S1); S2, calculating the length of the main vessel in each segmented image frame on the basis of the segmented images of the main vessel (S2); and S3, obtaining the blood flow rate in the main vessel on the basis of the calculated change of the lengths of the main vessel with time (S3). By using the method and apparatus for calculating the blood flow rate in a coronary artery and the electronic device, the automation of the calculation of the blood flow rate in a coronary artery is achieved, the calculated blood flow rate in the coronary artery is more accurate, and the calculation method is simple.

Embodiments include example systems, methods, and computer-accessible mediums for analysis of anatomical images for assessment of stenosis and disc degeneration. In some embodiments, systems, devices, and methods described herein include selecting a region of interest (ROI) in a three-dimensional (3D) volume of image data of a plurality of vertebra of a spine, identifying one or more anatomical parts in the ROI, determining one or more parameters of the one or more anatomical parts, and assessing a severity of a spinal deformity based on the one or more parameters.

Provided herein are imaging systems for a patient including an imaging probe and an imaging assembly. The imaging probe includes an elongate shaft with a rotatable optical core positioned within a lumen of the elongate shaft. The imaging probe further includes an optical assembly to direct light to tissue to be imaged and to collect reflected light from the tissue to be imaged. The system further includes an imaging assembly optically coupled to the imaging probe. The system further includes a processing unit with a processor and a memory coupled to the processor, and the memory stores instructions for the processor to perform an algorithm. The system records image data based on the reflected light collected by the optical assembly, such that the image data comprises data collected from a segment of a blood vessel during a pullback procedure. The algorithm can analyze the image data.