15 results about "Anatomical space" patented technology

The invention relates to the technical field of medical data processing and three-dimensional modeling, and discloses a skull thickness distribution diagram construction method and system fusing ultrasonic thickness measurement and optical localization. According to the method, an ultrasonic probe is used for obtaining a skull thickness value at a measuring point of the scalp of a subject, and meanwhile, a three-dimensional space coordinate of the measuring point is accurately determined through an optical navigation positioning system. The system binds the thickness value and the space coordinates in real time to form thickness-space data points, and performs multi-point repeated acquisition on the scalp surface, thereby constructing a three-dimensional thickness point cloud. And finally, the upper computer system performs interpolation processing on the point cloud data to generate a skull thickness distribution diagram with spatial continuity. According to the method, the defect that the skull thickness data and the anatomical space positioning information are mutually independent is overcome, accurate space-time correspondence of the measured value and the space position is realized, an individualized skull model can be constructed quickly at low cost, and an accurate sound field compensation calculation basis is provided for applications such as transcranial ultrasonic stimulation.

A method and apparatus are disclosed for puncturing and using the puncturing device to evaluate and identify the anatomical space that the puncturing device has entered. The physician can then determine if the puncturing device has entered the desired anatomical space or an unintended anatomical space.

The invention discloses a multi-anatomical structure space mapping method and system based on a medical image and a three-dimensional model, and relates to the technical field of medical image processing, and the method comprises the following steps: S1, obtaining a medical image data sequence according with a DICOM standard, analyzing and extracting DICOM header file information, automatically constructing a display interface of a multi-plane two-dimensional medical image view, and displaying the display interface of the multi-plane two-dimensional medical image view; the display interface at least comprises an axial plane view, a sagittal plane view and a coronal plane view which are mutually orthogonal; the external three-dimensional model is accurately aligned to the internal anatomical space of the patient by adopting the mapping and registering technology of the DICOM space information and the three-dimensional model in the general three-dimensional format, namely seamless loading and management of the medical image data and the general three-dimensional model in a unified platform are realized; and spatial alignment between three-dimensional models and medical images of different data sources is realized, so that the efficiency of consistent linkage display between a three-dimensional space and a two-dimensional section is greatly enhanced.

To provide an endoscopic instrument operated in a narrow anatomical space in a body by using an endoscope or an arthroscope.SOLUTION: The endoscope assembly comprises a handle and a shaft with an optical housing at its distal end, enclosing a camera sensor whose optical axis is at an angle to the shaft rotation axis. The camera sensor rotates with the shaft relative to the base housing of the handle. A rotation sensor in the handle senses an angle of rotation of the camera sensor relative to the base housing. The processor converts rotational changes in the field of view into translational changes to correct the angular orientation of the image from the image sensor. The processor applies variable smoothing to the rotation of the displayed image, the smoothing being greater during deceleration of the rotation than during acceleration of the rotation. The shaft is surrounded by a trocar, and the space between the shaft and the trocar allows irrigation fluid to be conveyed to and from the space at the distal end of the shaft.SELECTED DRAWING: Figure 91

The present disclosure relates to methods for performing minimally invasive anatomical space access, e.g., minimally invasive subretinal access (MISA), in connection with the delivery of therapeutic modalities to an anatomical space of interest, e.g., the subretinal space, and system components adapted to facilitate such delivery.

This invention pertains to the field of biomedical engineering technology and discloses a method, apparatus, equipment, product, and storage medium for constructing feature maps from MRI images to identify skull defects. Addressing the problem of existing automatic skull segmentation methods misclassifying defect areas as skull regions, this invention converts human brain MRI images to anatomical space based on multiple anatomical points and performs preliminary segmentation to obtain primary segmented regions of the skull. It calculates the coordinates of voxel points in the primary segmented region within the anatomical point coordinate system, establishes a matrix, calculates multiple MRI grayscale statistical features of the primary segmented region, and draws a feature map. Multi-condition feature threshold judgment is applied to the feature map to obtain a logical binary map, and regions with connected components greater than a specified threshold are extracted as skull defect areas. The method provided in this application utilizes multiple grayscale features to effectively correct the misidentification of the skull in existing technologies and can further be used to determine the filling tissue in skull defect areas, thereby improving the ability to identify skull defects.

A posterior nasal nerve dissection and retractor for laboratory mice, belonging to the field of medical device technology, solves the technical problem of limited anatomical space and inconvenient instrument operation during posterior nasal nerve resection in laboratory mice. The solution includes clamps, a limiting rack, and a supporting leaf spring. The inner side of the tail of one clamp handle is fixedly connected to one end of the limiting rack. A first locking hole is provided on the inner side of the tail of the other clamp handle, and the other end of the limiting rack is movably inserted into the first locking hole. The supporting leaf spring is cross-arranged within the area enclosed by the clamp handles and the limiting rack on both sides. Symmetrical light guide grooves are provided between the opposing surfaces of the two clamp heads, and symmetrical grooves are provided between the opposing surfaces of the outer ends of the two clamp heads. A dissector and a retractor are detachably installed in the grooves on both sides, respectively. A protective plate is detachably installed on the outer surface of the clamp head near the retractor. This invention provides a new tool for establishing a stable and reliable experimental mouse model of posterior nasal nerve resection.

This invention relates to the field of medical imaging diagnostic technology, specifically to a method and system for precise localization of small lesions in the breast and thyroid glands based on AI multimodal imaging. The method includes the following steps: acquiring ultrasound, X-ray, and magnetic resonance images of the breast and thyroid glands; extracting anatomical spatial location and imaging direction; calculating and mapping multimodal pixel spatial offsets; calculating scale consistency and normalizing response intensity based on co-located pixels; comparing multimodal intensity differences to assess consistency and form a scoring distribution; combining the score and intensity to adjust conditional probabilities; calculating joint probabilities and selecting spatial aggregates to locate small lesions. In this invention, by uniformly calibrating the spatial location and imaging direction of multimodal images, precise correspondence between different images at the same anatomical location is achieved. Multimodal response intensities are fused and consistency assessment is performed. Combining probability weight adjustment and spatial aggregation weakens the influence of noise in single images, enhances the common expression of small abnormal areas, and improves the stability and consistency of lesion localization.

The invention relates to the technical field of medical image processing, in particular to a general surgery department acute abdominal disease operation planning system based on AI image analysis, which comprises an image data acquisition module, a focus feature extraction module, an ischemia analysis module, an operation scheme construction module and a diagnosis result generation module. According to the method, uniform expression of multi-source data in space is guaranteed through numerical fitting and registration of an image sequence, multi-angle extraction of pathological features is achieved by combining quantitative indexes such as intestinal wall thickness, orifice expansion and hydrops density, and systematic marks are formed through deep learning feature fusion. A potential ischemic area can be quickly identified under the condition of complex abdominal lesion, accurate definition of a lesion range is realized by utilizing perfusion indexes and continuous section screening, and a relationship between lesion length and anatomical space is further calculated, so that a quantitative basis is provided for an operation excision range and an anastomosis condition; deviation caused by subjective judgment is reduced, and the pertinence and the executability of a treatment scheme are improved.

The present disclosure relates to tissue engineering devices for implant in an anatomical space in fascia of the human body comprising a scaffold made of porous absorbable material having a proximal portion for positioning within the fascia, a distal portion spaced from said proximal portion, a hollow central core extending between said proximal portion and said distal portion, and a sidewall surrounding said hollow central core; and a plurality of partially open, tissue engineering chambers formed in said side wall and radially arranged around said hollow central core, said tissue engineering chambers having an aggregate surface area greater than the fascia surface area in the anatomical space.

A processing device (1) and method for determining a position and / or orientation of a multi-hole grid template in a medical intervention procedure are disclosed. An anatomical space information processing unit (2) receives and / or processes data representing a target spatial volume in a body, and a grid position sampler (4) generates candidate positions of the grid template. A quality calculator (5) calculates for each candidate a quality measure indicative of a fitness of the candidate position of the grid template for the intervention procedure. A position selector (6) selects a position and / or orientation from the candidates based on the quality measures. For each candidate, a spatial relationship between each grid hole trajectory and the target volume is determined, and the quality measure takes at least this spatial relationship into account.

A system and method for anatomical structure segmentation and anatomical structure tracking is provided. The system receives an image from a camera assembly of the system. The image may include a representation of one or more anatomical structures of a target. The system extracts a visual representation from the image. The system determines position and orientation data associated with a robotic assembly of the system. The position and orientation data indicates a pose of the robotic assembly. The system generates a state representation based at least in part on the pose and the visual representation. The state representation indicates a state of the system. The system identifies one or more anatomical landmarks in an anatomical space in which the robotic assembly is operating. The system generates a plurality of segmentation maps. Each segmentation map identifies which anatomical structures should avoid contact with the robotic assembly.

The invention discloses a spine physiological anatomy key point positioning method based on deep learning. The method comprises the steps that a spine X-ray image, a spine CT image and a key point anatomy description text are acquired; performing feature extraction on the spine X-ray image and the spine CT image to obtain an X-ray feature map and a CT feature map, performing feature fusion on the X-ray feature map and the CT feature map to obtain a multi-modal fusion feature map, and performing feature extraction on the key point dissection description text to obtain text features; obtaining a thermodynamic diagram of each key point based on the multi-modal fusion feature map; obtaining the offset of each key point based on the multi-modal fusion feature map and the text features; wherein the offset prediction branch models an anatomical space relationship between key points through a graph convolutional network; and determining final coordinates of each key point based on the thermodynamic diagram and the offset. According to the method, the problems of insufficient single-modal feature expression, insufficient key point spatial correlation modeling and the like are solved, and accurate positioning of the spine physiological anatomy key points is realized.

The invention provides an analysis method and system based on gastroenterology department data, and the method comprises the steps: carrying out the triple semantic analysis of the medical concepts of the gastroenterology department, obtaining an anatomical space vector, a pathological space vector and a clinical space vector, forming a semantic vector of the gastroenterology department, obtaining a concept evolution relation between the medical concepts of the gastroenterology department, and carrying out the analysis of the medical concepts of the gastroenterology department; quantifying the cognitive distance weight of the concept evolution relationship, constructing a concept evolution relationship network through the evolution relationship and the cognitive distance weight, constructing a learning model, obtaining concepts mastered by intern doctors, learning behaviors and target learning concepts as input of the learning model, and outputting a learning path; the method comprises the following steps: constructing a semantic map database according to a digestive department semantic vector, an evolution relation network and learning model data, and generating a personalized learning scheme through the semantic map database and a learning path. Therefore, the accuracy and the suitability of the learning scheme in the training of the intern doctor in the digestive department are improved.

Surgical systems are provided. In one exemplary embodiment, a surgical system includes a first scope device, a first instrument, a second scope device, and a second instrument. The first scope device has a first portion configured to be inserted into an extraluminal anatomical space and a second portion configured to be positioned within an intraluminal anatomical space. The first scope device includes a first insufflation port configured to insufflate the intraluminal anatomical space. The first instrument is configured to be inserted through the extraluminal anatomical space and into the intraluminal anatomical space such that the first instrument is present in both the extraluminal and intraluminal anatomical spaces. The second scope device is configured to be inserted into the extraluminal anatomical space. The second scope device has a second insufflation port configured to insufflate the extraluminal anatomical space. The second instrument is configured to be inserted into the extraluminal anatomical space. Methods are also provided.