203 results about "Anatomical configuration" patented technology

The invention discloses an augmented reality intelligent navigation and operation quantitative evaluation method and system in an operating room, and the method comprises the steps: collecting multispectral image data and depth point cloud data of an operation region in the operating room in real time, and generating a multidimensional perception data set; performing feature extraction and spatial registration on the multi-dimensional perception data set, and decomposing the dynamic three-dimensional augmented reality model into an anatomical structure feature layer and an instrument interaction feature layer; performing dynamic matching and real-time rendering on the anatomical structure feature layer and the instrument interaction feature layer based on a digital twinning technology to generate augmented reality navigation information and an operation guidance scheme; and performing multi-dimensional quantitative analysis on the surgical operation process according to the augmented reality navigation information and the operation guidance scheme, and outputting a quantitative evaluation result. By utilizing the embodiment of the invention, augmented reality navigation guidance which is synchronous with a real operation scene in real time can be provided, meanwhile, accurate quantitative evaluation is carried out on the operation operation, and the accuracy, the safety and the trainability of the operation are improved.

The invention involves a system and method for increasing positional accuracy of surgical systems that utilize magnetic or electromagnetic sensors to provide positional awareness to a surgeon or robot performing the surgery. The system takes advantage of electromagnetic tracking through sensors. These sensors are very accurate and repeatable, while being compact enough to not inhibit surgical procedures. The accuracy and repeatability of the sensors is <1 mm within a predetermined 6 inch×6 inch performance motion box. The system is constructed and arranged to map the distortion patterns of the sensor and, in real time, correct the distortion pattern to provide accurate location of anatomical structures for performance of a surgery.

Systems, devices, and methods for integrating images from various sources and using the same to guide endoscopic procedures are disclosed. An endoscopic system comprises an endoscope to be positioned and navigated in a patient anatomy, and a processor configured to reconstruct a three-dimensional (3D) image of an anatomical target based on at least two images of the anatomical target. The at least two images can be calibrated and registered using respective landmarks. One or more secondary images can be integrated with the reconstructed 3D image. The reconstructed image or the integrated image, along with the endoscope navigation plan, can be displayed to a user. Based on the reconstructed or the integrated image, the processor can generate an endoscope navigation plan for use in an image-guided endoscopic procedure.

The invention discloses a myopia image deep learning recognition model training method, particularly relates to the technical field of medical image processing and deep learning, and is used for solving the problem that an existing deep learning model lacks anatomical structure priori knowledge guidance in myopia eye bottom image analysis. The method comprises the following steps: acquiring a myopia eye bottom image and anatomical structure priori knowledge data, extracting a multi-scale feature map by using a deep learning model, analyzing the geometric morphology of a key anatomical component based on standard spatial relationship information, and generating a spatial constraint loss item; according to the method, key anatomical path topology coherence is evaluated based on topology connection information, topology constraint loss items are generated, a loss item fusion strategy is dynamically adjusted according to a training stage, finally, a model is iteratively trained to convergence through a gradient back propagation algorithm, and organic combination of medical priori knowledge and a deep learning model is realized. And the clinical rationality and reliability of model output are improved.

Systems and methods are provided for multi-schema analysis of patient specific anatomical features from medical images. The system may receive medical images of a patient and metadata associated with the medical images indicative of a selected pathology, and automatically classify the medical images using a segmentation algorithm. The system may use an anatomical landmark detection algorithm leveraging Deep Reinforcement Learning (DRL) techniques to automatically locate one or more anatomical landmarks associated with the patient specific anatomical feature within the medical images. A 3D surface mesh model may be generated representing the patient specific anatomical features including the located one or more anatomical landmarks. The located one or more anatomical landmarks may be used to guide placement of a 3D model of a medical device that may be fused with the 3D surface mesh model to generate a patient specific 3D model of the medical device.

Systems and methods for clinical decision support are provided. One or more input medical images of an anatomical object of a patient are received. Characteristics of the anatomical object are extracted from the one or more input medical images. A risk associated with a medical procedure to be performed on the anatomical object is determined based on the one or more input medical images and the extracted characteristics of the anatomical object using one or more machine learning based risk assessment models. A simulation of the medical procedure is performed on the anatomical object based on the one or more input medical images, the extracted characteristics of the anatomical object, and the risk associated with the medical procedure. One or more clinical decisions associated with the medical procedure are automatically made based on the risk associated with the medical procedure and results of the simulation. The one or more clinical decisions are output.

Systems and methods for intraoperative tracking and visualization are disclosed. A current minimally invasive surgical (MIS) instrument pose may be determined based on a live intraoperative input video stream comprising a current image frame captured by a MIS camera. In addition, an instrument activation state and at least one parameter value associated with the instrument may also be determined. Intraoperative graphic visualization enhancements may be determined based on the activation state of the instrument, and / or a comparison of parameter values with corresponding parametric thresholds. The visualization enhancements may be applied to a current graphics frame. The current graphics frame may also include visualization enhancements related to proximate anatomical structures with proximity determined from the instrument pose and an anatomical model. The current graphics frame may be blended with the current input image frame to obtain an output blended image frame, which may form part of an output video stream.

Three dimensional virtual scene reconstruction of a medical procedure environment is provided. The system can include one or more processors, coupled with memory, to identify a frame that captures a scene in a medical procedure performed with a robotic medical system. The one or more processors can generate, using one or more models trained with machine learning, one or more masks that segment an anatomical structure in the frame, label the anatomical structure in the frame, and indicate a depth value for each pixel in the frame. The one or more processors can construct 3D mesh and texture data based on the one or more masks. The one or more processors can provide, in an interactive virtual environment, a virtual scene rendered using the 3D mesh and texture data generated from the frame that captures the scene in the medical procedure.

A surgical system is provided. The surgical system includes a robotic arm, a navigation system, and one or more controllers. The robotic arm includes a plurality of links and joints and is configured to support an end effector. The navigation system is configured to track a pose of an anatomy of a patient. The one or more controllers are configured to associate a target trajectory with the anatomy of the patient, define a trajectory selection zone associated with the target trajectory, operate the robotic arm in a free mode, whereby the robotic arm is freely moveable, responsive to the end effector being within the trajectory selection zone in the free mode, automatically select the target trajectory associated with the trajectory selection zone, and operate the robotic arm in an automatic mode, whereby the robotic arm is automatically moved to align the end effector with the target trajectory.

The invention discloses a clinical operation data analysis method based on virtual reality, and belongs to the field of virtual reality technology and medical skill training. Comprising the following steps: constructing a high-dimensional interaction data tensor covering space-time sequence features; establishing a three-dimensional space topological relation graph based on medical scene understanding, mapping various clinical operation skills into a three-dimensional model interaction sequence of a virtual medical device and an anatomical structure, and generating a multi-dimensional operation behavior feature vector matrix; virtual instrument operation sequence fragments with abnormal interaction efficiency or operation track deviation are identified, and dynamic loading priority weights of virtual medical scene resources are determined according to the virtual instrument operation sequence fragments; when the rendering frame rate of the virtual scene is lower than a specified threshold value, generating early warning information; and in a double-layer adaptive medical scene rendering optimization process, identifying performance bottleneck nodes and geometric processing conflicts in a three-dimensional rendering pipeline, and carrying out dynamic shader scheduling and model detail automatic switching according to a priority rule.

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.

The invention relates to a visual template generation method for a medical pathology report, and the method comprises the steps: obtaining a specimen image of a target case and an associated material block information list, carrying out the semantic segmentation model reasoning based on the content of the specimen image, recognizing and extracting a key anatomical structure region with morphological stability and clinical significance, and carrying out the recognition of the key anatomical structure region; according to the method, a group of sparse and reasonably distributed semantic anchor point coordinate sets are generated, the semantic anchor point coordinate sets are correlated with the original size of an image and then are stored in a structured manner, and the spatial topological relation between graphic elements and anchor points is used as a dynamic calibration basis, so that accurate positioning and consistent reproduction of annotations are realized. According to the scheme, the reducibility, the accuracy and the interaction consistency of pathological image annotation in a cross-equipment scene can be improved, and the efficiency and the reliability of pathological auxiliary diagnosis and remote cooperation are improved.

The suture threading device comprises a grip, an extension rod and a forceps head which are sequentially arranged in the length direction, and the grip is provided with an opening and closing operation piece for controlling the forceps head to be opened and closed; a movable joint is arranged between the extension rod and the forceps head, the forceps head is arranged to be suitable for moving in any direction relative to the extension rod through the movable joint, and the grip is provided with an angle operating part for driving the movable joint and a locking operating part capable of keeping the forceps head in a movable posture. According to the suture threading device, the movable joint can be driven through the angle operating part, so that the tong head can be switched to different angles according to different use scenes, and the flexible and convenient multi-angle adjusting capacity is provided to adapt to different anatomical structures and surgical admission paths; after the forceps head is adjusted to a proper angle, the movable joint is restrained through the locking operation piece, it is ensured that the posture of the forceps head is stable in the whole thread passing process, and therefore the accuracy and safety of an operation are improved.

An implantable medical device includes a first frame member. The first frame member includes a first set of elongate elements configured to conform to a patient's anatomy. The implantable medical device also includes a second frame member including a second set of elongate elements configured to conform to the patient's anatomy. The first frame member and the second frame member are discrete and separated from each other. The implantable medical device also includes a catheter portion disposed between the first frame member and the second frame member. The conduit portion includes a membrane connecting the first frame member and the second frame member.

The present disclosure includes methods (100, 200) for improving surgical accuracy and effectiveness in medical procedures by using an augmented reality system (300). The method (100, 200) involves: generating a preoperative plan in an augmented reality environment by visualizing a holographic representation of a patient's anatomy; recording program data according to the preoperative plan; using the recorded data to update the augmented reality system; and applying the updated system to establish a continuously improved feedback loop. According to the method, by integrating real-time data feedback into the operation process, the accuracy of the operation is improved, the effect of the patient is improved, the program is optimized, and continuous improvement of medical practice is promoted.

The buffer element may include a texture layer and a second layer disposed over the texture layer. The texture layer includes a plurality of protrusions extending upwardly from a surface of the texture layer. The second layer may include a plurality of recesses, each configured to receive a respective projection of the texture layer. The protrusions of the textured layer form a surface texture on the upper surface of the second layer when a load pressure is applied to the upper surface of the second layer (e.g., by a foot of a user). The cushioning elements may be used to form part of garments, accessories, athletic equipment, and / or articles of footwear, and may be configured to accommodate specific foot anatomy of a user, and / or may be customized to support a user's foot while performing an athletic activity.

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.

The present disclosure provides concepts for processing pixels of interest of a flat or curved 2D image plane in a 3D volume of an anatomical structure to generate a 2D image of the anatomical structure. The method includes, for each of the pixels of interest: determining a compounding direction associated with the respective pixel, the compounding direction being based, at least in part, on a shape of one or more features of the anatomical structure included in the 3D volume; identifying one or more compound pixels in the vicinity of the respective pixel in the 3D volume based on the compounding direction; and determining an updated value of the respective pixel based on values of the compound pixels. The method further includes generating the 2D image based on the updated values of the pixels of interest. For each of the pixels of interest, a gradient of a feature of the anatomical structure included in the 3D volume in the vicinity of the respective pixel is identified, and the compounding direction is determined further based on the identified gradient. The method allows for adaptive compounding based on the shape of the anatomical structure included in the 3D volume, such that blurring and ghosting artifacts are reduced, while maintaining the benefits of compounding techniques (e.g., noise reduction).

Systems and methods of virtual reality or augmented reality (VR / AR) visualization of 3D medical images using a VR / AR visualization system are disclosed. The VR / AR visualization system includes a computing device operably coupled to a VR / AR device, and the VR / AR device includes a holographic display and at least one sensor. The holographic display is configured to display a holographic image to an operator. The computing device is configured to receive at least one stored 3D image of an anatomical structure of a subject and at least one real-time 3D position of at least one surgical instrument. The computing device is further configured to register the at least one real-time 3D position of the at least one surgical instrument to correspond to the at least one 3D image of the anatomical structure of the subject, and generate the holographic image including the at least one real-time position of the at least one surgical instrument overlaid on the at least one 3D image of the anatomical structure of the subject.

A system is disclosed that includes an optical tracking device and a surgical computing device. The optical tracking device includes a structured light module and an optical module that includes an image sensor and is spaced from the structured light module at a known distance. The surgical computing device includes a display device, a non-transitory computer readable medium including instructions, and processor(s) configured to execute the instructions to generate a depth map from a first image captured by the image sensor during projection of a pattern into a surgical environment by the structured light module. The pattern is projected in a near-infrared (NIR) spectrum. The processor(s) are further configured to execute the stored instructions to reconstruct a 3D surface of anatomical structure(s) based on the generated depth map. Additionally, the processor(s) are configured to execute the stored instructions to output the reconstructed 3D surface to the display device.

A surgical system for computer-assisted navigation during a surgical procedure includes at least one processor that obtains a 3D radiological representation of a target anatomy of a patient and a fiducial set of a registration fixture. An attempt is made to register a position of the fiducial set in the 3D radiological representation to a 3D imaging space tracked by a camera tracking system. Based on a determination that one fiducial of the fiducial set has an unsuccessful registration to a position of the 3D imaging space, the following operations are performed: displaying at least one view of the 3D radiological representation having a graphical overlay indicating that the fiducial has an unsuccessful registration to the 3D imaging space; receiving user-provided position information identifying where the fiducial is located in the 3D radiological representation; and registering the position of the fiducial to the 3D imaging space based on the user-provided position information.

The invention relates to the technical field of medical image processing, in particular to an anatomical structure segmentation system and method for a medical image, and the system comprises a data preprocessing module which is used for carrying out the standardized preprocessing of an input medical volume data image, and outputting the standardized image data. According to the invention, the data preprocessing module unifies the distribution of medical images of different sources, and the double-branch segmentation network module fuses the detail resolution capability of a two-dimensional network and the topology perception capability of a three-dimensional network, and especially optimizes the recognition precision and boundary coherence of a low-contrast region. And the feature fusion module realizes complementary enhancement of multi-scale features, so that the discrimination reliability of multi-class segmentation is further improved. Besides, the post-processing module effectively filters noise and smoothes the boundary, so that the output segmentation result has good spatial consistency and can be directly used for three-dimensional reconstruction, and the segmentation precision and robustness are improved.

Provided are a computer program product, system, and method for training a pose estimation model to determine anatomy keypoints in images. A teacher network, implementing machine learning, processes images representing anatomies to produce heatmaps representing keypoints of the anatomies. An anatomy parsing network, implementing machine learning, processes the images to produce segmentation representations labeling anatomies represented in the images. The segmentation representations from the anatomy parsing network and the heatmaps from the teacher network are concatenated to produce mixed heatmaps. A pose estimation model, implementing machine learning, is trained to process the images to output predicted heatmaps to minimize a loss function of the output predicted heatmaps from the pose estimation model and the mixed heatmaps.

The invention relates to the technical field of source applicator dose optimization, in particular to an after-loading 3D printing source applicator optimization design method based on deep learning, which comprises the following steps: S1, acquiring medical image data and clinical dose constraint conditions of a target object, and calculating the clinical dose of the target object based on the medical image data; constructing a three-dimensional anatomical topology network reflecting the spatial relationship and attribute of the anatomical structure; and S2, through the three-dimensional anatomical topology network, through an adaptive structure generation process, determining an initial source applicator biological form configuration and a structure parameter set thereof. An initial source applicator parameter is generated from a medical image through a deep learning model, and optimization is performed in combination with clinical dose constraints, so that the optimal dose is achieved while the final model is ensured to fit an anatomical structure of a patient.

An implantable medical device comprising a first frame component. The first frame component including a first set of elongate elements configured to conform to an anatomy of a patient. The implantable medical device also comprising a second frame component including a second set of elongate elements configured to conform to an anatomy of a patient. The first frame component and the second frame component being discrete and separate from one another. The implantable medical device also comprising a conduit portion arranged between the first frame component and the second frame component. The conduit portion including a membrane connecting the first frame component and the second frame component.

A method performed by a computing system comprises receiving a fluoroscopic image of a patient anatomy while a portion of a medical instrument is positioned within the patient anatomy. The fluoroscopic image has a fluoroscopic frame of reference. The portion has a sensed position in an anatomic model frame of reference. The method further comprises identifying the portion in the fluoroscopic image and identifying an extracted position of the portion in the fluoroscopic frame of reference using the identified portion in the fluoroscopic image. The method further comprises registering the fluoroscopic frame of reference to the anatomic model frame of reference based on the sensed position of the portion and the extracted position of the portion.

A guidance system is configured to detect a current pose of an ultrasound transducer and to determine a movement to achieve a desired pose associated with a desired view or imaging plane of a patients anatomy. In one embodiment, the guidance system includes a processor circuit in communication with the ultrasound transducer. The processor circuit is configured to: receive an input associated with a desired pose of the ultrasound transducer; receive ultrasound imaging data representative of a field of view of the ultrasound transducer in a current pose; determine a movement to align the current pose of the ultrasound transducer with the desired pose; and generate a graphical representation of the movement. The graphical representation shows both the current pose of the ultrasound transducer and the desired pose of the ultrasound transducer. The graphical representation is output to a display in communication with the processor circuit.

Embodiments of the present disclosure provide a surgical robot system may include an end-effector element configured for controlled movement and positioning and tracking of surgical instruments and objects relative to an image of a patient's anatomical structure. In some embodiments the end-effector and instruments may be tracked by surgical robot system and displayed to a user. In some embodiments, tracking of a target anatomical structure and objects, both in a navigation space and an image space, may be provided by a dynamic reference base located at a position away from the target anatomical structure.

Various embodiments are directed to generating a contour object for a region of interest represented by medical data corresponding to internal anatomy of a patient. Respective display coordinates are determined by performing a transformation on the medical data of the contour object. The display coordinates correspond to a unified three-dimensional (3D) space of an Augmented Reality (AR) environment. Respective edges of the contour object are displayed according to trace points. The trace points are portrayed in the AR environment as a visual outline in alignment with an ultrasound imagery visualization of the region of interest in the patient's physical internal anatomy. The trace points are registered as internal landmarks for the region of interest in the patient's physical internal anatomy.

Medical devices and instruments, particularly appliers that may be used to apply occlusion devices such as occlusion clips on anatomical structures, are disclosed. Some example clip appliers may include an activation lever configured to open and close an occlusion clip releasably mounted in an end effector. Some example clip appliers may include a deployment trigger configured to release the occlusion clip from the end effector. Some example clip appliers may include a shaft extending between a handle and the end effector that is rotatable and / or bendable.