Provided is a medical image processing apparatus including: an image acquisition unit that obtains a medical image of a subject; and an image processing unit that generates a second medical image by applying predetermined image processing on the medical image. The image processing unit includes: a surface area extraction unit that extracts a surface area including information that can lead to individuality determination or identification of the subject, from the medical image; a body orientation determination unit that determines body orientation on the basis of the surface area; a surface area deformation unit that deforms the surface area of the medical image; and an object assignment unit that assigns an object indicating the body orientation to the medical image in which the surface area has been deformed and that generates the second medical image.

A method for determining an optimized weighting of an encoder and decoder network; the method comprising: for each of a plurality of test weightings, performing the following steps with the encoder and decoder operating using the test weighting: (a) encoding, using the encoder, a reference image and a distorted image into a latent space to form an encoding; (b) decoding the encoding, using the decoder, to form a distortion map indicative of a difference between the reference image and a distorted image; (c) spatially transforming the distorted image by the distortion map to obtain an aligned image; (d) comparing the aligned image to the reference image to obtain a similarity metric; and (e) determining a loss function which is at least partially defined by the similarity metric; wherein the optimized weighting is determined to be the test weighting which has an optimized loss function.

Device, system, and method of generating a reduced-size volumetric dataset. A method includes receiving a plurality of three-dimensional volumetric datasets that correspond to a particular object; and generating, from that plurality of three-dimensional volumetric datasets, a single uniform mesh dataset that corresponds to that particular object. The size of that single uniform mesh dataset is less than ¼ of the aggregate size of the plurality of three-dimensional volumetric datasets. The resulting uniform mesh is temporally coherent, and can be used for animating that object, as well as for introducing modifications to that object or to clothing or garments worn by that object.

A workpiece image search apparatus includes: a workpiece image deformation unit that generates a third workpiece image by deforming a second workpiece image so that a difference in workpiece shape between a first workpiece image and the second workpiece image becomes smaller, wherein the first workpiece image is obtained by projecting a first workpiece shape of a first workpiece on a two-dimensional plane, and the second workpiece image is obtained by projecting a second workpiece shape of a second workpiece on a two-dimensional plane; and a similarity calculation unit that calculates a similarity between the first workpiece shape and the second workpiece shape by comparing the third workpiece image with the first workpiece image.

A method, apparatus and system for calculating stress parameters is provided. The method comprises establishing a first image pyramid according to an image of a sample before deformation, and establishing a second image pyramid corresponding to the first image pyramid according to an image of the sample after deformation; starting from a top level in the first image pyramid, iteratively calculating displacement information on each level in the first image pyramid relative to a corresponding level in the second image pyramid based on a center point of each sub-region at each level in the first image pyramid and other positions in the sub-region; calculating strain information on the sample according to displacement information on a bottom level of the first image pyramid; and calculating stress parameters of the sample based on the strain information.

Sparse phase unwrapping is disclosed. A first image and a second image are received. The first image and the second image are coregistered. The first image and the second image comprise respective phase data. An unwrapped interferogram is generated, including by solving an optimization problem using a nonconvex penalty function, where minimizing the penalty function produces sparse minimizers.

An orientation device, an orientation system and an orientation method are provided. The orientation device includes a seat body, a pressure sensor, and a computing unit. The seat body includes a bearing surface, and the seat body is non-directional. The pressure sensor is disposed below the bearing surface. The pressure sensor is configured to obtain a plurality of pressure data of the bearing surface when an object is disposed on the bearing surface. The computing unit is coupled to the pressure sensor. The computing unit is configured to analyze the pressure data to obtain a direction data. The direction data is configured to determine a first direction of the seat body.

Embodiments of the present disclosure disclose an image processing method and apparatus, an image device, and a storage medium. The image processing method includes: obtaining an image; obtaining first rotation information of each of multiple nodes of a target; determining second rotation information of each child node with respect to a parent node in the multiple nodes of the target according to a hierarchical relationship among the nodes and multiple pieces of the first rotation information; and controlling movements of nodes in a controlled model corresponding to the multiple nodes based on multiple pieces of the second rotation information.

Systems and methods for automatically excluding artifacts from an analysis of a biological specimen image are disclosed. An exemplary method includes obtaining an immunohistochemistry (IHC) image and a control image, determining whether the control image includes one or more artifacts, upon a determination that the control image includes one or more artifacts, identifying one or more artifact regions within the IHC image by mapping the one or more artifacts from the control image to the IHC image, and performing image analysis of the IHC image where any identified artifact regions are excluded from the image analysis.

A method is provided for machine vision and image analysis for recognizing an object in an electronic image, which is captured with the aid of an optical sensor. A reference image of the object to be recognized is trained during a learning phase and compared with the image of the scene during a working phase, the pattern comparison between the object and the scene takes place with the aid of a modified census transform, using a determination of maximum and which must exceed a threshold value for a positive statement on a degree of correspondence.