A method and apparatus for registering a first image having a first plurality of pixel values from a sensor having a plurality of pixels and a second image having a second plurality of pixel values of the plurality of pixels is disclosed. The method includes selecting a first image having a first plurality of pixel values and a second image having a second plurality of pixel values, grouping the first plurality of pixels according to a grid having a plurality of grid elements, each grid element having a plurality of pixels, determining a grid element displacement of the second image from the first image for each grid element of pixels, filtering the displacement of the second image from the first image to produce filtered valid grid element displacements and invalid grid element displacements, and determining a warping transform of each of the grid element displacements.

A medical imaging system (200) includes a masking unit (234), an image registration unit (238), a motion estimator (240) and a motion compensating reconstructor (244). The masking unit constructs a mask for each reconstructed volumetric phase image of a plurality of reconstructed volumetric phase images that masks portions of a corresponding image external to an anatomical model fitted to a segmented at least one anatomical structure, 5 wherein the plurality of reconstructed volumetric phase images include a target phase and a plurality of temporal neighboring phases reconstructed from projection data. The image registration unit registers the masked reconstructed volumetric phase images. The motion estimator estimates motion between the target phase and the plurality of temporal neighboring phases according to the model based on the registered masked reconstructed 10 volumetric phase images. The motion compensating reconstructor reconstructs a motion compensated medical image from the projection data using the estimated motion of the registered masked reconstructed volumetric phase images.

A method for determining respiratory induced blood mass change from a four-dimensional computed tomography (4D CT) includes receiving a 4D CT image set which contains a first three-dimensional computed tomographic image (3D CT) and a second 3D CT image. The method includes executing a deformable image registration (DIR) function on the received 4D CT image set, and determining a displacement vector field indicative of the lung motion induced by patient respiration. The method further includes segmenting the received 3D CT images into a first segmented image and a second segmented. The method includes determining the change in blood mass between the first 3D CT image and the second 3D CT image from the DIR solution, the segmented images, and measured CT densities.

An image processing apparatus according an exemplary embodiment of the present invention estimates for a plurality of positions in a target image an estimated value of an error in registration for acquiring a third three-dimensional image by deforming at least one of a first three-dimensional image of a subject and a second three-dimensional image, one of the three-dimensional images being the target image, designates a cross section in the target image, acquires a statistical value of the error in the designated cross section based on the estimated value estimated for a plurality of positions in the cross section, and displays the statistical value.

The present invention relates to a system for extracting position information of object in point cloud data by using component comprising a component file creating unit making the component file of prior standardized object; an object position information extraction unit extracting position information of object by using point cloud data collected by LiDAR; and an object outline extraction and position determination unit optimizing object outline of point cloud data by using the component file, and extracting accurate information of standard position from the optimized outline.

A face replacement system for replacing a target face with a source face can include a facial landmark determination model having a cascade multichannel convolutional neural network (CMC-CNN) to process both the target and the source face. A face warping module is able to warp the source face using determined facial landmarks that match the determined facial landmarks of the target face, and a face selection module is able to select a facial region of interest in the source face. An image blending module is used to blend the target face with the selected source region of interest.

Methods, systems, and computer readable media for automated intraoperative surgical guidance in medical images are disclosed. A system and method generally for analyzing subject image data, calculating surgical decision risks and autonomously providing recommended pathways or actions that support the decision-making process of a surgeon to predict optimized implant and subject outcomes (ex. implant guidance, fracture reduction, anatomical alignment) by a graphical user interface.

The present invention relates to a computer-implemented method, a computer program product, and a server for positioning a structural element in a 2D section of a CAD structure. The invention is characterized in that at least two distances, each distance in between an alignment line of the structural element and a parallel reference line of the 2D section, are displayed on a user visualization means and dynamically updated as the location of the structural element within the 2D section is changed. In a preferred embodiment, the reference lines are dynamically chosen based on the location of the structural element within the 3D section.

An imaging system is provided. The imaging system includes a 3D image capture device, which is configured to capture a depth image of an object, and a thermal image capture device, which is configured to capture a thermal image of the object. The imaging system also includes a processing system, which is coupled with the 3D image capture device and the thermal image capture device. The processing system is configured to process the depth image and the thermal image to produce a thermal-depth fusion image by aligning the thermal image with the depth image, and assigning a thermal value derived from the thermal image to a plurality of points of the depth image.

The present disclosure relates to a method for use in adaptive radiotherapy and a treatment planning device. The method may comprise accessing a first medical image and a second medical image that represent a region of interest of a patient at different times. Each medical image is segmented into a target region and at least one non-target region. The method may further comprise accessing a deformation vector field including a plurality of vectors, wherein each vector defines a geometric transformation to map a respective voxel in the first medical image to a corresponding voxel in the second medical image. The method may further comprise generating a modified deformation vector field by: identifying a first vector in the deformation vector field that maps a voxel in the first medical image to a voxel that is in a non-target region in the second medical image; and determining whether the first vector causes a distance between the mapped voxel and the target region to increase and, if so, reducing the magnitude of the first vector. The method may further comprise post-processing the modified deformation vector field to compensate for changes in the shape or size of the target region.