286 results about "Anatomic region" patented technology

A neurophysiological magnetic stimulation (NMS) method includes obtaining motor thresholds over one or both motor strips adhered to the patient's head or the equivalent anatomic region for treatment of non-brain, nervous system disorders. The method further includes applying magnetic stimulation coils to a therapeutic target region of the patient's brain, brainstem, spinal cord, or peripheral nervous system and applying NMS in increasing amplitudes as tolerated over the course of treatment.

The invention discloses a CBCT (Cone Beam Computed Tomography) high-quality CT (Computed Tomography) image synthesis method based on structure prior guidance, which comprises the following construction steps of patient data collection and arrangement, space guidance deformable attention convolution, structure prior guidance type conditional diffusion image synthesis and reasoning process and quality evaluation. The method specifically comprises the steps of technical design of a space guiding module, technical design of a deformable sampling kernel generator, technical design of an attention weight modulator, contour extraction operation, diffusion modeling operation, conditional denoising network design and target training. The method provided by the invention has the advantages of structural perception, high spatial selectivity, high modulability and the like; and the reduction precision of the model on the key anatomical region is enhanced by taking a contour map as a structure priori condition. The whole diffusion generation network realizes unification of local detail reservation and global structure stability while maintaining noise robustness, and gradually generates a high-quality pseudo CT image which is close to a real CT modal and has excellent structure consistency.

The invention discloses a heart image processing method and device, a storage medium and computer equipment, and relates to the technical field of nuclear medicine image processing and quantitative analysis. The method comprises the steps that a heart image to be processed is acquired, four cavities of the heart image are segmented based on a pre-trained segmentation model, segmentation masks are obtained, and the heart image is a CT image or an MR image; aligning the heart image into a PET space, so that the segmentation mask is mapped to a PET image corresponding to the heart image, and a PET segmentation image is obtained; and cutting the PET segmented image based on the segmentation mask to obtain a PET target anatomical region, and performing three-dimensional rendering on the PET target anatomical region to obtain a dynamic rendered image of tracer agent distribution. According to the method, the segmentation precision of the myocardial subregion can be improved, and the three-dimensional visualization effect of the heart image and the processing efficiency of the heart image are improved.

The present invention concerns extensible absorbent pads for wound dressings. The absorbent pad has a plurality of fenestrations therein, wherein the fenestrations are arranged in a pattern about a central point. The pattern comprises one or more fenestrations having symmetry about a cardinal axis and one or more fenestrations having symmetry about an intercardinal axis, wherein the cardinal and intercardinal axes cross at the central point. The absorbent pads of the present invention can be used in advanced wound care dressing applications where additional stretch and extensibility of the dressing will assist clinicians in applying the dressing to difficult to dress anatomical areas.

The invention discloses a thoracoscope-assisted intelligent navigation system and method for thoracic surgery, and the method comprises the steps: recording the respiratory capacity of a patient and shooting a focus image in a breathing state, precisely calculating the position change amplitude and range of a focus in a breathing process, and drawing a dynamic graph for visual presentation; selecting an electromagnetic navigation system positioning method and performing preoperative planning according to lesion characteristics and positions, and adopting a transbronchial or transthoracic navigation positioning technology; wherein different anatomical regions of a human body are divided according to the focus position and the anatomical structure, a navigation path algorithm is planned for each anatomical region, parameters of the electromagnetic navigation system are adjusted according to the characteristics of tissues passed by the navigation path, and final positioning is confirmed; the television is combined with the thoracoscope to assist the thoracoscope, so that the focus is accurately marked and cut off; according to the method, the safety and success rate of the operation are improved, operation wounds are reduced, better treatment effect and experience are brought to patients, and the method conforms to the development trend of precision and intelligence of the medical technology.

Threaded bone implants, such as pedicle screws, are provided with an elongate body comprising a first portion, a second portion distal to the first portion, and a third portion distal to the second portion. The first, second and third portions may be provided with different features that correspond to first, second and third anatomical regions of interest in a vertebrae or other bone segment(s). The bone implants, systems, methods of manufacture, and methods of use disclosed herein may be used for the stabilization, fixation and / or fusion of the sacroiliac joint, the spine and or other bone segments.

Methods and systems are disclosed for enhancing blood flow to anatomical regions. An applicator may include a stimulation portion operative to define a protrusion extending from the applicator. Positioning the applicator in relation to the anatomical region may emplace the protrusion upon a predetermined area thereof, resulting in stimulation being applied thereto. A blood flow enhancement device can be used alongside the applicator to apply suction, heating, and / or vibration effects to the anatomical region, via the blood flow enhancement device having a vacuum, an ultrasonic transducer and / or a vibrator. An inner surface of the applicator's protrusion may receive a portion of the blood flow enhancement device, allowing a user to impart these effects upon the predetermined area the protrusion is associated with. The combination of stimulating, heating, vibrating, and / or suctioning the anatomical region in this manner can allow treatments like therapies, diagnostics, and pleasure to be administered to a user.

A method for generating a virtual model of an object in a patient's anatomy. The method employs a surface scan of an anatomical region of the patient's oral cavity and a volumetric density scan of the anatomical region. The method includes receiving a first dataset of labeled surface scan segments, receiving a second dataset of labeled volumetric density scan segments, cross-mounting in a coordinate system, labeled surface scan segments from the first dataset to labeled volumetric density scan segments from the second dataset, receiving identification of the targeted extraction object, identifying the 3D volumetric density model and the 3D surface model associated with the volumetric density scan segment label, and generating a third dataset comprising and 3D model of a socket, a 3D model of portions of a tooth crown, a 3D model of portions of a target extraction tooth, and / or a 3D model of the extraction contour.

The invention relates to the technical field of medical image processing, and discloses a radiotherapy patient body surface contour monitoring and correction method and system, and the method comprises the steps: obtaining original point cloud data from the body surface of a patient through combining a three-dimensional scanning device, a stereoscopic microscope and an infrared sensor, and generating a high-resolution body surface contour model, dividing the body surface into a plurality of monitoring blocks based on a preset anatomical region division rule; local dynamic change features are extracted through time sequence analysis, correction guidance parameters are generated in combination with positioning information of an offset area, and a correction model is constructed to obtain a collaborative correction instruction set. And finally, correction is carried out based on the collaborative correction instruction set, whether correction succeeds or not is judged through a non-rigid registration technology, and if not, adjustment is carried out until correction succeeds. According to the method, the dynamic change of the body surface contour of the patient can be monitored and corrected in real time, accurate treatment positioning in the radiotherapy process is ensured, and the treatment effect and safety are improved.

A 3-dimensional tracking and navigation simulator system for image guided neuro-endoscopy, said system comprising: a fiducial based physical model of an anatomic region associated with neuro-endoscopy, wherein the physical model is mapped with CT / MRI slices of the anatomy; a virtual model of the anatomic region associated with neuro-endoscopy; at least one surgical instrument operable to perform neuro-endoscopy, said at least one surgical instrument is associated with a 3-D tracking component; a camera unit for tracking a location of the at least one surgical instrument with the 3-D tracking component, relative to a reference unit of the physical model; one or more displays for displaying the location of the at least one surgical instrument in the CT / MRI slices and endoscopic output, a computer work-station operably coupled to the physical model, and the camera unit, said work-station comprising: a localization and tracking module having configured to track the tasks performed by a user with the at least one surgical instrument, and estimate the position and rotation of the at least one surgical instrument in 6 degrees of freedom; a virtual space mapping module configured to map a location to a corresponding anatomic position in the virtual model to give a navigation of the surgical instrument in the virtual model; an evaluation module configured to evaluate the 3D tracking of tasks performed based on a localization metric and a 3D tracking metric, and provide feedback to the user based on the performance using machine learning and AI based algorithms.

Systems and methods are provided for reducing the reliance on operator skill during vascular ultrasound procedures. The placement of an ultrasound probe to assess perfusion associated with a wound may be facilitated by receiving input suitable for identifying an anatomical region associated with the wound and providing an indication of a suitable initial probe position, and optionally, probe orientation, for acoustically interrogating a target arterial vessel known to provide perfusion to the anatomical region associated with the wound. Regions exhibiting arterial flow may be detected as the probe is moved, enabling arterial vessel detection and localization. A subregion within the detected arterial vessel and a beam steering angle may be autonomously determined for spectral Doppler data collection, enabling the measurement of hemodynamic measures associated with the arterial vessel. Example apparatus for securing the probe to the patient and facilitating probe positioning to search for a target vessel are disclosed.

Systems and techniques are disclosed to identify and monitor side effects and treatment outcomes relating to neurostimulation programming. An example technique to identify a side effect relating to neurostimulation programming includes: obtaining neurostimulation programming parameters to be used in a neurostimulation device of a patient; obtaining source data that defines effects of neurostimulation treatment in an anatomical area of the patient; modeling use of the neurostimulation programming parameters in the anatomical area of the neurostimulation treatment, based on the source data, to determine a predicted side effect; and outputting information that identifies characteristics of the predicted side effect.

A technique is provided for tracking an object in a real-time time series of medical images. A method, performed by a downstream neural network, NN, includes receiving a real-time time series of medical images of a patient's anatomical region at an input layer of the NN. Using a spatio-temporal encoder, the real-time time series is encoded, and an encoded representation per frame is obtained. A frame corresponds to a medical image at a time instance within the real-time time series of medical images. Using a multi-head cross-attention, MCA, decoder, the encoded representation of a most recent frame is decoded. The MCA decoder correlates the most recent frame with a predefined number of preceding frames. An object is tracked. The tracking comprises determining coordinates of the object based on the decoded most recent frame.

A deep-learning based framework to assess the quality of medical image auto-segmentation is described. According to an example, a computer-implemented method comprises receiving segmentation masks generated, via one or more segmentation models, from medical image data depicting an anatomical region of a subject, wherein each of the segmentation masks depicts a different anatomical structure of a set of different anatomical structures included in the anatomical region. The method further comprises generating reconstructed versions of the segmentation masks based on application of a multi-channel reconstruction model to the segmentation masks, wherein the reconstructed versions correspond to optimized versions of the segmentation masks. The method further comprises determining an assessment of quality of the segmentation masks based on comparison of the segmentation masks to the reconstructed versions, generating output data regarding the assessment of quality, and rendering the output data via an electronic output device.

A tracking system and a method for 3D tracking of a medical device, equipped of at least one ultrasound sensor, inside an anatomical region of a subject having at least one layer of a first tissue type at least partially surrounding a volume having at least one second tissue type, wherein the properties of ultrasounds propagation in the first and second tissue type are different.

A device and system for real-time visualization of the electrophysiologic activity of a brain, particularly at the cortical surface. The neural device can acquire, process, and display high-spatiotemporal-resolution electrophysiologic data in real-time across entire electrode arrays spanning many thousands of electrodes over identified anatomic regions. The system is compatible with thin-film cortical surface electrodes that record from neural tissues without damaging those tissues. The system can be used to guide diagnostic and therapeutic actions with high precision, and also provides the basis for a brain-computer interface.

An electromyography (EMG) measurement device includes a garment configured to be worn on an anatomical region of an associated wearer, a plurality of electrodes arranged on the garment to contact skin of the anatomical region when the garment is worn on the anatomical region of the associated wearer, electronics operatively connected with the plurality of electrodes and configured to measure EMG data emanating from the anatomical region, and an electronic processor programmed to derive a contribution of spatial muscle activity of a target muscle or muscle group to the measured EMG data.

The invention discloses an MAP scoring method and device based on kidney three-dimensional modeling, and belongs to the field of medical image processing. The method comprises the following steps: acquiring kidney medical image data, wherein the kidney medical image data comprises kidney CT image data; preprocessing the kidney medical image data; generating a complete kidney three-dimensional model based on the kidney medical image data; calculating the centroid positions of all voxels in the renal vein three-dimensional model, and taking the Z coordinate of the centroid as a standard measurement plane; identifying an anatomical region needing to be measured on the standard measurement plane based on a deep learning segmentation model; extracting an outer contour of the kidney based on the kidney three-dimensional model, determining a posterior abdominal wall contour based on the front edge of the lumbar major muscle, and calculating the shortest distance between the outer contour of the kidney and the posterior abdominal wall contour; and determining a perirenal fat region, enhancing the strip-shaped structure by using a multi-scale filter, and calculating the proportion of the strip-shaped structure in the perirenal fat region. According to the invention, objective quantitative evaluation of perirenal fat adhesion risk is realized.

The invention relates to organ segmentation quality assurance based on deep learning for medical images. A deep learning-based framework for assessing the quality of automatic segmentation of medical images is described. According to an example, a computer-implemented method includes receiving segmentation masks generated via one or more segmentation models from medical image data depicting an anatomical region of a subject, where each of the segmentation masks depicts a different anatomical structure of a set of different anatomical structures included in the anatomical region. The method further includes generating a reconstructed version of the segmented mask based on applying a multi-channel reconstruction model to the segmented mask, wherein the reconstructed version corresponds to an optimized version of the segmented mask. The method further includes determining a quality assessment of the segmented mask based on comparing the segmented mask to the reconstructed version; generating output data regarding the quality assessment; and presenting the output data via an electronic output device.

A system may comprise a processor and a memory having computer readable instructions stored thereon. The computer readable instructions, when executed by the processor, may cause the system to receive anatomic image data for an anatomic area and segment the anatomic image data to identify an anatomic passageway in the anatomic area. The computer readable instructions may also cause the system to identify a gap between a first segment and a second segment of the segmented anatomic image data, generate a bridge segment to bridge the gap, and generate an anatomic model of a diseased lung including the first segment, the second segment and the bridge segment.

The invention provides a radiographic image report generation method and system of a CT image, and the method comprises the steps: firstly transmitting an input CT image into a region division module, carrying out the whole-organ segmentation of the image, then distributing a whole-organ segmentation result according to a preset anatomical region with clinical significance, obtaining an anatomical region image with clinical significance, and carrying out the whole-organ segmentation according to a preset anatomical region with clinical significance. An anatomical area image with clinical significance is sent to a report generation module, an area image report text is generated, the report text and an original image are sent to a text-driven focus detection module, the position of a focus in the image is obtained and reported, and a doctor modifies the area image report and then sends the area image report to a report writing module to generate a final report. And meanwhile, the report modified by the doctor and the report automatically generated by the model are sent to an AI report generation quality evaluation module, so that the model carries out immediate update learning.

An apparatus includes a memory to store first volumetric image data representing a first volumetric image of an anatomical region having a volume of interest (VOI). The first volumetric image includes several first voxels at first locations in the first volumetric image. The first volumetric image data includes first uncertainty values corresponding to the several first voxels. The first uncertainty values represent probabilities that the corresponding plurality of first voxels are part of the VOI. The memory is to store second volumetric image data representing a second volumetric image of the anatomical region. The apparatus includes a processing device operatively coupled to the memory. The processing device is to determine a deformation field to map the several first voxels to second locations in the second volumetric image. The deformation field is based in part on the first uncertainty values.

The invention discloses an acupuncture positioning method based on image processing. The method comprises the following steps: S1, generating preprocessed medical human body image data; s2, generating a semantic segmentation image, and calibrating each anatomical region and a specific acupuncture point region of a human body from the semantic segmentation image; s3, generating a candidate acupoint region heat map based on the semantic segmentation image and the multi-scale standardized acupoint region heat map template; s4, performing alignment matching on the candidate acupoint region heat map and a standardized acupoint region heat map database by utilizing structure-guided heat map matching to obtain a matched acupoint result, wherein the standardized acupoint region heat map database comprises standard acupoint distribution information; and S5, integrating the matched acupuncture point result with clinical data of the patient to form a personalized acupuncture point candidate set, selecting a final acupuncture target meeting a heat map responsivity threshold and an individual adaptation condition, and outputting an acupuncture positioning result according to the final acupuncture target. According to the invention, the treatment relevance and clinical practicability of target recommendation are improved, and the operability and safety of intelligent acupuncture treatment are enhanced.

A computer-implemented method (100) of identification regions of ischemia areas in the left ventricle, the method comprising: receiving (105) a CT Coronary Angiogram scan data representing a 3D volume of a region of anatomy that includes a pericardium; segmenting (110) the CT scan data to obtain a cardiac anatomical model; applying (110) a cardiac anatomical model to a machine-learning algorithm to identify a region of ischemia, while the machine-learning model is trained on a data sets comprising a spatially aligned CT and perfusion data.

An electromyography (EMG) measurement system includes a garment configured to be worn on an anatomical region, electrodes arranged on the garment to contact skin of the anatomical region when the garment is worn on the anatomical region, electronics connected with the electrodes to measure EMG data emanating from the anatomical region, and an electronic processor programmed to filter the EMG data to suppress or remove artifacts using filters computed using approximate joint diagonalization of covariance (AJDC) matrices or by transforming the EMG data to source signals using iteratively adjusted forward filters.

Provided in embodiments of the present application are a positioning assistance method and a medical imaging system. The positioning assistance method includes: obtaining image data captured via an image capture apparatus and including a subject, the image data including optical image data and depth image data; determining, according to the image data, a direction indication line representing at least one anatomical region of interest; and calculating a body region inclination angle according to the direction indication line, the body region inclination angle including at least one of a first included angle and a second included angle, the first included angle representing an included angle between an anatomical region of interest and a plane on which hardware of a medical imaging system is located, and the second included angle representing an included angle between two anatomical regions of interest.

The invention relates to the technical field of medical image processing and three-dimensional reconstruction, and particularly discloses a reconstruction and analogue simulation method based on a cardiac image. The method comprises the following steps: firstly, preprocessing an input CT or MRI medical image, and automatically segmenting a heart multi-tissue structure by using an nnUNetv2 model, including a plurality of anatomical regions such as atrium, ventricle, myocardial tissue and blood pool; and then performing topology repair, smoothing processing and label resampling on the segmentation result to obtain a three-dimensional label body with a continuous structure and a complete boundary. And based on the optimized tag body, constructing a heart three-dimensional surface model by adopting a Marching Cubes algorithm, and generating a multi-material volume grid suitable for finite element analysis. According to an electrode position and a radio frequency parameter set by a user, a radio frequency ablation simulation model based on a Pennes biological heat conduction equation and an Arrhenius model is established, a temperature field and a tissue thermal damage range are calculated, and a simulation result is displayed in a three-dimensional mode in an overlapping mode. According to the method, the integrated process from medical image automatic segmentation to heart three-dimensional reconstruction and thermal simulation is realized, the segmentation precision, the modeling efficiency and the simulation reliability are improved, and the method can be applied to application scenes such as surgical planning, preoperative evaluation and medical teaching.

The invention discloses a region-level retrieval enhanced multi-view chest radiography report generation method. According to the method, pairwise cross attention fusion is carried out on multi-view chest radiograph image features, and feature mapping is carried out to serve as a visual prompt for inputting a large language model. A chest radiograph anatomical region-level knowledge base containing a plurality of semantic entities is established, and each entity contains region features, region tags, entity description and lesion tags of an anatomical region. Different anatomical areas are obtained by adopting a detection algorithm for an input chest radiograph image, and text descriptions of entities corresponding to the related anatomical areas are retrieved from a knowledge base to serve as text prompts of a large language model. And finally, the large language model generates a corresponding diagnosis report by adopting an autoregression generation mode based on visual prompt, text prompt and a report generation instruction. According to the method, feature fusion is effectively carried out on the multi-view chest radiograph images, the prior knowledge of the chest radiograph images in the anatomical area level is effectively fused into the report generation process, and the method is suitable for the field of chest radiograph report generation.

A computer-implemented method of predicting a status of an embolization procedure on an aneurism, includes: receiving (S110) projection image data (110) representing temporal blood flow in a region of the anatomy including the aneurism during the embolization procedure; inputting (S120) the received projection image data (110) into a neural network (120) trained to predict temporal blood flow (130), wherein the neural network (120) is trained to predict temporal blood flow (130) using training data (140) representing temporal blood flow in a region of the anatomy that does not include an aneurism; and in response to the inputting (S120): generating (S130) an output (160) indicative of the status of the embolization procedure based on the predicted temporal blood flow.

A method comprises displaying image data of an anatomical region via a display system, determining a target location in the anatomical region, and determining an anatomical boundary based on the target location. The anatomical boundary indicates a surface of an anatomical structure in the anatomical region. The anatomical structure is to be avoided by a tool extendable from a medical instrument. The method further comprises determining a trajectory zone around a path between a distal end of the medical instrument and the target location. The target location is between the distal end of the medical instrument and the anatomical boundary. The method further comprises determining a zone boundary based on an intersection of the trajectory zone with the anatomical boundary.