31 results about "Anatomical configuration" patented technology

The present disclosure relates to support members for use in bras and other garments. The support members can be manufactured through additive manufacturing, subtractive manufacturing methods, and injection molding techniques, among others. The support members can include a thickness gradient designed to support a breast. The support members can be customized according to the anatomical configuration of a particular user. The support members can include one or more biometric sensors.

An orthopaedic surgical instrument system includes a sensor adapter and multiple surgical instruments. The sensor adapter includes a housing with a force sensor positioned within the housing and a sensor contact configured to transfer force to the force sensor extending from the housing. Each surgical instrument includes a sensor connector configured to receive the sensor adapter at a predetermined location relative to the surgical instrument. Each sensor adapter further includes a registering feature to engage an anatomical feature of a patient or another surgical instrument. The surgical instruments may include a shim that may be attached to a gap assessment tool or a tibial insert trial. Methods associated with the surgical instrument system are also disclosed.

This teaching relates to estimating 3D camera pose based on 2D features detected from 2D images. A virtual 3D camera pose is generated relative to a 3D model of a target organ and associated anatomical structures. Virtual 2D images are created by projecting the 3D model from a viewpoint determined based on the virtual 3D camera pose. Each virtual 2D image includes the 2D structure of the target organ and / or some 3D anatomical structures visible from the corresponding viewpoint. A 2D feature / camera pose mapping model is then obtained based on the 2D features extracted from the virtual 2D images and the corresponding virtual 3D camera pose, where the 2D features include 2D ridge lines projected from 3D ridges on the target organ represented in the 3D model.

A method includes randomly selecting both a subset of subjects from a plurality of subjects and one or more medical images from different protocols for each respective subject of the subset of subjects. The method includes obtaining an encoder-decoder framework. The method includes pretraining an encoder of the encoder-decoder framework with the one or more medical images from different protocols for each respective subject of the subset of subjects utilizing self-supervised learning with a physics informed contrastive loss function to generate a trained protocol invariant encoder configured to be utilized for different downstream tasks, wherein utilizing the physics informed contrastive loss function promotes similar latent space features to be extracted from of the one or more medical images of a same subject while repelling latent space features from different subjects, and wherein the similar latent space features represent a same underlying anatomical structure.

This invention provides a virtual laparoscopic digital twin method, device, and storage medium. The method includes the following steps: constructing a three-dimensional anatomical model based on the patient's preoperative medical imaging data; planning the virtual laparoscopic spatial travel path in the model coordinate system and dividing it into path sub-intervals corresponding to each clinical scenario; pre-setting key nodes in each sub-interval and defining the anatomical structure set of each node, integrating them to form a path prior model; during the operation, segmenting real-time laparoscopic video to identify anatomical structures and surgical instruments; extracting semantic features based on the segmentation results of multiple consecutive frames and determining the current state of the surgical scenario; matching the corresponding sub-interval from the path prior model according to the current scenario state and updating the laparoscopic advancement parameters; when advancing to the vicinity of a predefined node, triggering a viewpoint switch and adjusting the laparoscopic viewpoint to the preset pose corresponding to the node. This invention solves the problem in the prior art that the virtual viewpoint cannot automatically and stably advance with the progress of the operation.

An association of a pre-operative plan and tracked position and orientation of a surgical instrument relative patient anatomy in a navigation system is generated. The pre-operative plan includes a virtual representation of the patient anatomy data. Position and orientation of the patient anatomy as well as position and orientation of the surgical instrument within the navigation system is obtained. A virtual representation of the surgical instrument relative the virtual representation of the patient anatomy data is generated in multiple orientations in separate parts of a split window. A system with a tracker comprising a tracker interface for attaching the tracker to the instrument includes a surgical navigation module for generating the virtual representation in a split window.

The subject application presents an automated medical procedure system featuring accurate spatial calibration and registration capabilities. The system comprises a calibrated robotic subsystem with a position-accurate arm, a tracking subsystem, and processor-based modules for registration and calibration. Key innovations include the use of factory-defined geometric configurations for targets, systematic spatial recalibration before each procedure, and the ability to perform both rigid point-to-point and point cloud registrations. These features enable the system to maintain accurate spatial relationships between components and patient anatomy, allowing for highly accurate and adaptable automated medical procedures across various specialties.

This application discloses an optimization method, apparatus, and storage medium for dynamic hovering arcs, relating to the fields of medical technology and radiotherapy technology. The method includes: acquiring an initial control point sequence for the dynamic intensity-modulated arc; determining candidate hovering angles based on the modulation complexity of each angle in the initial control point sequence; increasing the number of control points in the initial control point sequence based on the candidate hovering angles to form a hybrid control point sequence; and adjusting the accelerator-executed plan based on the hybrid control point sequence using a multi-objective optimization function. This application solves the technical problem of insufficient modulation freedom in key beam directions in existing volumetric rotational intensity-modulated radiotherapy (VMAT) techniques when dealing with complex anatomical configurations.

Embodiments for rendering an operative guidance overlay in association with a patient are disclosed. A method includes receiving image data indicating an anatomical structure of the patient and a structure of operative instruments; generating virtual models based on the image data; receiving sensor data associated with a user, the operative instruments, or the patient; dynamically generating guidance overlay data associated with the anatomical structure of the patient, or the operative instruments based on the virtual models and the sensor data; and rendering the operative guidance overlay in association with the patient based on the guidance overlay data using a wearable augmented reality interface device. The virtual models include a virtual anatomical model of the anatomical structure of the patient, or virtual instrument models associated with the operative instruments. The rendering comprises continuous alignment of the virtual anatomical model with the patient and the virtual instrument models with the operative instruments.

Surgical tracking systems and methods employ multiple tracking devices, each incorporating a controller, camera, and wireless communication interface. Each tracking device can detect other tracking devices through its camera and can be detectable by cameras of the other tracking devices. The controllers determine the relative pose of a target anatomy and the relative poses among the tracking devices. Pose information is wirelessly shared to establish a common coordinate system in which the target anatomy is localized. The controllers detect a tracking conditions or criteria to dynamically select a subset of tracking devices to track the target anatomy within the common coordinate system.

This invention discloses a medical image processing method, apparatus, electronic device, storage medium, and program product. The method includes: acquiring a first medical image of a target area and a corresponding clinical text report; generating an image processing strategy based on a pre-built strategy generation model, according to the first medical image and the clinical text report; wherein the first medical image includes at least two medical images of different modalities; registering the first medical image according to the image registration strategy and the pre-built image registration model to obtain a second medical image and a deformation field; the deformation field is used to describe the displacement degree of each voxel in the first medical image during the registration process; fusing the second medical image according to the image fusion strategy, the deformation field, and the pre-built image fusion model to obtain a third medical image. This method can significantly improve the registration accuracy of anatomical structures between images of different modalities and effectively enhance the credibility and interpretability of the fused image.

This application provides a method and related apparatus for generating surgical safety boundaries based on time-varying anisotropic distance transformation and multi-level safety surface metadata encapsulation. The method includes: S1. Obtaining a binary mask of key anatomical structures and their corresponding anatomical categories; S2. Performing time-varying settings on anisotropic parameters based on the anatomical category and the current surgical stage; S3. Performing anisotropic Euclidean distance transformation on the binary mask based on the anisotropic parameters; S4. Extracting multi-level safety isometric surfaces from the anisotropic distance field based on multi-level distance thresholds; S5. Encapsulating the multi-level safety isometric surfaces and complete metadata into a safety boundary data package; S6. Traceably exporting based on various standard 3D model file formats. This application also provides related apparatus corresponding to the method, including devices, electronic devices, computer-readable storage media, and computer program products.

A surgical computing device may include a processor configured to implement two neural networks, a primary neural network trained with a procedure focus and support neural network trained with a patient focus. Data indicative of a surgical patient, a target procedure, and a proposed procedure plan may be input to the support neural network. The support neural network may generate a patient specific mapping from this data. The patient specific mapping and the data indicative of a surgical patient, a target procedure, and a proposed procedure plan may be input to the primary neural network. The primary neural network may output a modified procedure plan that is different from the proposed procedure plan. In an example, the support neural network is trained to isolate anatomical elements. And the primary neural network is trained to identify procedure plans associated with improved patient outcomes. Such a two-network approach may facilitate the use of diverse training data sets to better refine procedure plans for a variety of uses.

Intraoperative stereotaxic navigation system 10 for determining an orientation of a surgical tool (12) relative to a patient's anatomy located within a surgical environment (16). The system (10) includes a radar-based sensor (18) which is operable to define a field-of-view FOV 20 and determine at least one of relative distance to, direction to, and orientation of, one or more objects in the FOV 20, and a mount (24) configured to releasably secure the sensor (18) to one of the patient (26) and the tool (12) to allow the other of the patient (26) and the tool (12) to be within the FOV 20. A processor (28) is communicatively connectable with the radar-based sensor (18) and configured to determine the orientation of the tool (12) responsive to receiving at least one of relative distance, direction and / or orientation information, from the sensor (18), relating to at least one of the patient (26) and the tool (12), and receiving information relating to orientation of the patient (26) relative to the surgical environment (16).

This invention discloses a medical image segmentation system and method, belonging to the field of medical image processing technology. The invention segments each slice in a three-dimensional medical image to be segmented, taking into account the anatomical continuity between slices during segmentation. For each slice I along the Z-axis, its preceding and following adjacent slices in the Z-axis direction are extracted, constructing a slice sequence containing three consecutive adjacent slices as input to the medical image segmentation system. Then, feature extraction is performed on slice I based on an encoder-decoder structure. A differential gating unit is introduced at the jump connection between the encoder unit and the corresponding decoder unit in the decoder to fuse inter-layer information of the slices into the feature extraction process of slice I, achieving accurate representation of slice features and avoiding "faults" in the Z-axis direction. This improves the accuracy of segmenting medical images with significant anisotropic features.

The present application relates to the technical field of medical image processing, in particular to an image synthesis method for digital anesthesia teaching. The present application acquires an ultrasound image as a background image, a simulated anesthesia teaching element image as a foreground image, sets a target operation type and patient physiological characteristic parameters; performs anatomical structure segmentation on the background image to obtain anatomical structure distribution information and determine the target position of the foreground image; extracts an anatomical boundary, calculates an internal distance field and an external distance field, constructs a spatial fusion weight in combination with a category label and a confidence degree; determines an acoustic parameter from a decay degree score in a decay-acoustic parameter mapping table, performs acoustic characteristic matching processing on the foreground image, and then performs weighted fusion with the background image to obtain a synthesized image; and updates the instrument position and posture frame by frame along an operation path to generate a sequence of synthesized images. The present application realizes individualized physiological characteristic driven ultrasound simulation teaching image synthesis.

A method for an interactive medical record review, said method comprising the steps of: displaying at-a-glance anatomical imagery with health code and / or date of event associated with a patient interaction on a whole-body graphic; and configuring the anatomical imagery on the whole-body graphic for pointing-device control enabling a requester to access and interact with the code-standardized data related to the patient interaction.

This paper provides a medical imaging system and method that eliminates the need for segmentation to provide navigation and procedural planning. One method includes receiving three-dimensional image data of a patient's anatomy by a medical imaging system having at least one processing device. The method also includes filtering the three-dimensional data to display a portion of the three-dimensional image data associated with the patient's anatomy, and receiving input from an operator input device at the processing device. The input includes navigation directions for virtual movement within a space defined by the three-dimensional image data. The method further includes tracking the virtual movement and generating a first model of the patient's anatomy based on the tracked virtual movement.

This document describes a medical system, device, and related method, comprising a medical system including a lead, the lead including a distal portion and a proximal portion. The distal portion may be configured to transition from an expanded configuration to a straightened configuration. In the expanded configuration, the distal portion may be configured to be anchored to a target site in an anatomical structure. The medical system may also include a porous body coupled to the distal end of the tube. The tube may include a first lumen and a second lumen. The first lumen may be configured to receive at least the proximal portion of the lead, and the second lumen may be configured to be coupled to a suction source.

A computer-implemented method for displaying medical image data is provided. The method comprises receiving medical image data indicative of a patient anatomy having multiple connected parts that are movable relative to each other, creating at least two different bounding boxes in the medical image data so that each bounding box comprises image data indicative of at least one respective part of the patient anatomy not indicated by the image data of another one of the bounding boxes, and simultaneously displaying images, wherein each of the images is associated with a different one of the at least two different bounding boxes. A computer program, a carrier and a surgical planning system are also provided.

The present application discloses a radiotherapy positioning and dose optimization system based on deep learning and multimodal image fusion, including a multimodal image acquisition and fusion module, a tumor positioning module, an organ motion tracking module, a dose optimization calculation module, and a quality assurance and verification module; the multimodal image acquisition and fusion module is configured to compatibly and integratively integrate data generated by a plurality of medical imaging devices, and accurately match and fuse different modal images in three-dimensional space through an advanced image alignment algorithm, to form a high-precision fusion image containing information on anatomical structure, functional metabolism, and physiological activities.

Fully automated computer-implemented deep learning techniques of contrast-enhanced cardiac MRI segmentation are provided. The techniques may include providing cardiac MRI data to a first computer-implemented deep learning network trained in order to identify a left ventricle region of interest to generate left ventricle region-of-interest-identified cardiac MRI data. The techniques may also include providing the left ventricle region-of-interest-identified cardiac MRI data to a second computer-implemented deep learning network trained in order to identify myocardium to generate myocardium-identified cardiac MRI data. The techniques may further include providing the myocardium-identified cardiac MRI data to at least one third computer-implemented deep learning network trained to conform data to geometrical anatomical constraints in order to generate anatomical-conforming myocardium-identified cardiac MRI data. The techniques may further include outputting the anatomical-conforming myocardium-identified cardiac MRI data.

A computer-implemented method for displaying medical image data is provided. The method comprises receiving medical image data indicative of a patient anatomy having multiple connected parts that are movable relative to each other, creating at least two different bounding boxes in the medical image data so that each bounding box comprises image data indicative of at least one respective part of the patient anatomy not indicated by the image data of another one of the bounding boxes, and simultaneously displaying images, wherein each of the images is associated with a different one of the at least two different bounding boxes. A computer program, a carrier and a surgical planning system are also provided.

This invention relates to the field of ophthalmic information storage, and discloses a method and system for storing ophthalmic image feature information. First, anatomical structural features are extracted from raw ophthalmic images after processing, and then semantically bound to standardized clinical terms and research tags to generate a ternary feature dataset. A hybrid storage architecture consisting of blockchain and distributed nodes is constructed, clarifying data interaction rules and a traceability information synchronization mechanism. A multi-dimensional association index is built to support multi-dimensional dynamic retrieval. The ternary feature data is hierarchically compressed and de-identified based on a federated learning framework. An abnormal access behavior monitoring mechanism is established. A secure sharing service with hierarchical permissions is provided. A backup cycle is set, and rapid data recovery is achieved. This invention solves the problems of existing technologies that rely on single-keyword matching for retrieval, resulting in low retrieval efficiency, insufficient accuracy, difficulty in meeting multi-dimensional retrieval needs, large data redundancy, and a lack of intelligent monitoring of abnormal access behavior.

This invention belongs to the field of medical image processing technology, specifically relating to a deformable medical image registration method based on dynamic graph convolutional attention. It aims to address problems in existing technologies such as imbalance between global and local feature modeling, high computational cost, and poor adaptability to large deformations. This method acquires multi-level features from both moving and stationary medical images through a weighted dual-stream feature extraction encoder. It adaptively enhances the representation of similar anatomical structures using a dynamic feature fusion module, accurately captures global spatial dependencies and local details using a dynamic graph convolutional attention module, and iteratively optimizes the deformation field through a multi-stage deformation fusion strategy from coarse to fine, ultimately generating a precise and stable final deformation field to complete image registration. This invention effectively balances global modeling and local characterization capabilities, reduces model computation and memory usage, improves registration stability and anatomical structure alignment accuracy in large deformation scenarios, and balances registration efficiency with the physical rationality of the deformation field. It provides efficient and reliable medical image registration support for clinical scenarios such as computer-aided diagnosis and image-guided surgery.

The present disclosure relates generally to a surgical system. The surgical system includes one or more surgical instrument assemblies and / or a surgical navigation system. The surgical instrument assembly includes a tracking device that can be tracked by the surgical navigation system. The surgical system is also configured to allow a user to define one or more alert zones related to the patient’s anatomy and / or a surgical procedure path. The surgical system further includes an alert device in communication with the surgical navigation system such that the alert device is configured to provide a user-perceptible alert to a surgeon or medical staff based on a location of the surgical instrument relative to the defined alert zones and / or the surgical procedure path as determined by the surgical navigation system.

The present disclosure relates to remote medical examination of a patient, and, more specifically, to a remote exam attachment that, along with a user device, may capture images of an anatomical feature for examination of a patient. The remote exam attachment may include a lens and may couple to an examination tool, such as a speculum, a scope, or a tongue depressor, which may be used with a camera of the user device. The user device may be configured to adjust one or more settings of the camera, such as the zoom, field of view, aperture, and / or the like. The user device may further be configured to transmit an image captured in conjunction with the remote exam attachment to another user device. Accordingly, the remote exam attachment, along with the user device, may capture, display, and / or transmit images of an anatomical feature, facilitating remote examination of a patient.

Human anatomical structures are extracted from medical images. A foundation model is generated by learning the human anatomical structures, resulting in generic representations of the human anatomical structures. The human anatomical structures are learned by executing a self-supervised contrastive learning framework to conserve hierarchical relationships of the human anatomical structures in the medical images and to capture distinct representations for different human anatomical structures at different granularity levels. The self-supervised contrastive learning framework executes an anatomy decomposer (AD) to conserve hierarchical relationships of the human anatomical structures in the received medical images and executes a purposive pruner (PP) to capture distinct representations for different human anatomical structures at different granularity levels. Medical images that form no part of the received medical images may then be processed using the trained foundation model.

A medical device-placing system including a medical-device tip-location sensor (“TLS”) configured for placement on a chest of a patient, an ultrasound probe, a console, and an alternative-reality headset. The ultrasound probe can be configured to emit ultrasound signals into the patient and receive echoed ultrasound signals from the patient. The console can be configured to transform the echoed ultrasound signals to produce ultrasound-image segments corresponding to anatomical structures of the patient, as well as transform TLS signals from the TLS into location information for a medical device within the patient. The alternative-reality headset can include a display screen through which a wearer of the alternative-reality headset can see the patient. The display screen can be configured to display over the patient a virtual medical per the location information for the medical device within objects of virtual anatomy corresponding to the ultrasound-image segments.