16 results about "3d registration" patented technology

The present application relates to the field of robot and embodied intelligent robot technology, and particularly relates to a visual guidance robot hand-eye collaborative calibration method and system. It comprises: collecting three-dimensional information of geometric features of a mechanical arm in a plurality of groups of postures in a mechanical arm base coordinate system and joint angles of the mechanical arm; extracting two-dimensional geometric features corresponding to the three-dimensional information; solving an initial hand-eye calibration matrix; using an optimization algorithm based on geometric feature reprojection error to optimize the initial calibration matrix; according to the calibration results between each mechanical arm base coordinate system and the camera coordinate system, further solving the relative pose relationship between each mechanical arm base coordinate system. The present application determines the pose relationship between the mechanical arm base coordinate system and the camera coordinate system and between each mechanical arm base coordinate system by using the hand-eye collaborative calibration method combining 2D-3D registration technology, mechanical arm error modeling and geometric feature reprojection optimization algorithm, and has the advantages of fast speed, high precision and no need for external calibration objects.

The present invention relates to technical field of 2D-3D registration, it proposes a 2D-3D registration method based on joint localization, comprising: S1: obtaining a coordinate transformation matrix between the biplane X-ray system and the joint localization device; S2: capturing anteroposterior / lateral X-ray images by using the biplane X-ray system, and recording a first spatial position and a first gravity direction of the joint center using the joint localization device; S3: establishing a coordinate system with the joint center of the 3D bone joint model as the coordinate origin, and determining a second gravity direction; converting the first spatial position and the first gravity direction recorded by the joint localization device into the coordinate system of the biplane X-ray system via the coordinate transformation relationship; S4: matching the coordinate origin and the second gravity direction of the 3D bone joint model with the first spatial position and the first gravity direction to complete coarse 2D-3D registration; S5: taking the result of the coarse registration as an initial value for fine registration based on iterative optimization to complete fine 2D-3D registration. This method improves the convergence, accuracy, and efficiency of the registration.

A method for registration of digital medical images is provided. The method includes the step of storing a 3D digital medical image having a 3D anatomical feature and a first coordinate system and storing a 2D digital medical image having a 2D anatomical feature and a second coordinate system. The method further includes the steps of storing a placement of a digital medical object on the 3D digital medical image and the 2D digital medical image and generating a simulated 2D digital medical image from the 3D digital medical image, wherein the simulated 2D digital medical image comprises a simulated 2D anatomical feature corresponding to the 3D anatomical feature. The 2D anatomical feature is compared with the simulated 2D anatomical feature until a match is reached and a registration of the first coordinate system with the second coordinate system based on the match is determined.

A system, method, medium, and implementation for registering an ultrasound probe in laparoscopic ultrasound surgery, and its applications are disclosed. The two-dimensional (2D) position of the ultrasound probe in a 2D laparoscopic (LP) image is detected, wherein the LP camera has been previously calibrated in three-dimensional (3D) space. Based on the detected 2D position of the ultrasound probe and the ultrasound model used for the probe, the 3D pose of the deployed ultrasound probe is estimated and registered in 3D space.

The application discloses a laparoscopic liver surgery navigation 2D / 3D registration method based on a PSO-SoftPOSIT combined algorithm, the method first obtains a global optimal pose through PSO algorithm iteration as an initial pose of the SoftPOSIT algorithm, then further registers the initial pose through the SoftPOSIT algorithm, and re-adds the obtained pose to the PSO algorithm, through iteration, finally the method not only solves the problem that current surgery navigation registration related algorithms can only use expensive binocular endoscopes, but also reduces the requirement of the SoftPOSIT method on the initial pose, and higher registration accuracy and better registration effect are achieved.

The challenge is to reduce the adverse effects of the head restraint when aligning medical images that include the head restraint. [Solution] When aligning image A, which is a FLAIR image, with image B, which is a CT image showing a head restraint, first, the head restraint shown in image B is removed. Then, by performing 3D registration analysis on image B' and image A after this removal process, the same area as a certain part in image A' is displayed in image B''. For example, the positions of the cross-shaped cursors in image A' and image B'' indicate the same area.

Systems and methods are provided for accomplishing fast and accurate 3D registration of curves and surfaces using local differential information, i.e., normals and tangents. In an embodiment, a method solves the curve-vs-surface alignment problem either by using a purely online search scheme, or by taking advantage of the availability of a pre-operative model, which often happens in medical procedures, to further speed-up the computational search by performing offline processing of the pre-operative bone model. The disclosed method is also extended to solve the curve-vs-curve and surface-vs-surface alignment problems, which also have important applications in medical procedures such as arthroscopy and arthroplasty.

A method for registration of digital medical images is provided. The method includes the step of storing a 3D digital medical image having a 3D anatomical feature and a first coordinate system and storing a 2D digital medical image having a 2D anatomical feature and a second coordinate system. The method further includes the steps of storing a placement of a digital medical object on the 3D digital medical image and the 2D digital medical image and generating a simulated 2D digital medical image from the 3D digital medical image, wherein the simulated 2D digital medical image comprises a simulated 2D anatomical feature corresponding to the 3D anatomical feature. The 2D anatomical feature is compared with the simulated 2D anatomical feature until a match is reached and a registration of the first coordinate system with the second coordinate system based on the match is determined.

The invention discloses a fracture reduction path planning system and method based on image data, and the method comprises the steps: carrying out the fine anatomical structure segmentation of high-resolution preoperative image data, firstly constructing a three-dimensional bone block model and a three-dimensional high-risk soft tissue model, carrying out the meshing of the three-dimensional bone block model and the three-dimensional high-risk soft tissue model based on anatomical map data, and carrying out the risk assignment, a predictive static probability risk field network is obtained; in the operation process, 2D-3D registration and tracking are conducted through intraoperative imaging data, real-time displacement information of a key tracking point is obtained, then the static probability risk field network is dynamically updated, and an updated probability risk field network capable of reflecting current soft tissue real deformation is formed; and finally, based on the updated risk field and the current pose of the robot, self-adaptive adjustment of a local path is carried out, so that a safe and efficient fracture reduction path is accurately planned. In this way, the precision and safety of the fracture reduction surgery are remarkably improved.

A method for correcting location of a virtual target in a patient during a live procedure comprises segmenting the organ and the real target from an initial pre-procedure image data set; receiving a live procedure image data set of the patient including the organ and the real target and camera tracking information; registering the initial pre-procedure image data set and the live image data set; determining a candidate location of a virtual target for the real target based on the initial registration; generating a first image at a first view angle showing the virtual target and the real target; adjusting the candidate location of the virtual target to match the actual location of the real target in the first image; and computing a corrected location for the virtual target based on the adjusting step. Related systems are disclosed.

This application discloses a registration method, system, electronic device, and storage medium for femoral fractures. The method includes converting femoral CT volume data into a three-dimensional coordinate system to generate a volume data model; adjusting pose parameters to generate a target DRR image that coincides with the anatomical structure of the X-ray image; identifying anatomical key points jointly recognized by both and obtaining their corresponding two-dimensional coordinates; and then solving for the three-dimensional coordinates of these key points. Subsequently, a target function is constructed by combining the three-dimensional coordinates of the key points and the two-dimensional coordinates of the X-ray image; the optimal pose parameters of the model are solved with the function minimization as the objective; and finally, an optimal DRR image that precisely coincides with the X-ray image is generated based on these parameters. This method achieves precise 2D / 3D registration of femoral fractures using X-ray and CT scans, improving the robustness and accuracy of the registration, and providing a reliable three-dimensional pose reference for the diagnosis and treatment of femoral fractures.

A system for performing touchless registration of patient anatomy includes memory storing instructions and one or more processing devices configured to execute the instructions. Executing the instructions causes the system to obtain, from a camera, an image of the patient anatomy, the image including a laser projection that is projected onto the patient anatomy using a laser projector, detect the laser projection in the image obtained from the camera, obtain a three-dimensional set of points corresponding to the detected laser projection, and register the patient anatomy by storing data correlating the patient anatomy to the three-dimensional set of points.

The invention discloses a hip joint prosthesis three-dimensional registration method based on a CT image, and relates to the technical field of hip joint prosthesis registration, and the method comprises the steps: S1, reconstructing a patient femur three-dimensional structure based on the CT image through 3D slicer software, and carrying out the segmentation and extraction of two-dimensional features of a target part of the three-dimensional structure; by constructing a complete technical process of three-dimensional reconstruction and two-dimensional feature extraction, precise positioning of anatomical mark points, comprehensive analysis of the proximal femur form and registration of a prosthesis size algorithm, the problems in the prior art are effectively solved, and by combining the ICP algorithm with a mark point positioning mode of global and local registration, the positioning accuracy of the femur is improved. Dependence on manual operation and empirical judgment is eliminated, the defect that individual anatomical difference adaptation is insufficient is overcome, accurate mapping of mark points is achieved, the medullary cavity form analysis method combining multi-plane intersection with two-dimensional and three-dimensional feature fusion makes up for the defect that in the prior art, medullary cavity form analysis is not comprehensive, and accurate data support is provided for registration.

The application discloses a kind of serial section electron microscope three-dimensional registration trajectory optimization method based on neural ordinary differential equation, belong to electron microscope three-dimensional reconstruction technical field.The present application regards each pixel as particle in continuous medium, sets single particle trajectory optimization objective function and global consistency trajectory constraint objective function;Using two-dimensional U-shaped convolutional neural network estimates the displacement field between adjacent slices, and constructs the time sequence trajectory body of each pixel;Combining gauss-siedel iteration with neural ordinary differential equation carries out trajectory smoothing;The optimized trajectory is inverted into displacement field on pixel grid, based on final objective function carries out network training, finally realizes the registration of image stack.The present application is completely supervised training, especially suitable for the scene of serial section electron microscope of annotation scarcity, and a large number of experiments on multiple data sets covering different tissue types show that the method is superior to existing methods in terms of structure recovery accuracy and cross-organ robustness.

Methods and systems for enhancing colors in a set of images. The method includes: acquiring input data including 3D data and image data, the image data being a set of single images, each image having a portion overlapping other images and consisting of a plurality of pixels, each pixel providing radiation measurement information; performing a joint integration on the input data to create integrated data, the joint integration including a 3D registration of the 3D data and the image data, a spatial graph decomposition that generates the structured representation, and a multi-homography decomposition that estimates homography in the image data; performing multi-scale feature extraction and block-by-block feature embedding on the integrated data, thereby integrating features of the 3D data and the image data in a single feature vector and embedding both geometric information and radiation measurement information; based on block-by-block feature embedding, generating a block-by-block weight map for each homography in the overlapped part; a pixel-by-pixel correction is performed in the set of images based on the weight map to generate a set of corrected images with homogenized radiation measurement information.