A silhouette-based limb finder may be used to detect limbs from a camera image. This limb determination may be used to control an application, such as a game, or a combination with other image processing. A first distance field indicating a distance from the edge of a silhouette in an image and a second distance field indicating distance from a location in the silhouette may be used to generate a path from an extremity point on the silhouette to the location. This path then may be used to determine a limb in the silhouette. This allows tracking of limbs even for hard to detect player poses.

A method of anatomic classification of blood vessel anatomy in aneurysms includes the steps of accessing an image of a blood vessel, analyzing the image to identify a point of divergence of the blood vessel and one or more additional points of reference of the blood vessel. One or more distances are then measured between the point of divergence of the blood vessel and at least one of the one or more additional points of reference. The aneurysm is then classified based upon the measured distances. A method of treatment of an aneurysm in a blood vessel further includes implanting one or more devices within the blood vessel for treatment of the aneurysm.

A computer system is provided that includes a camera device and a processor configured to receive scene data captured by the camera device for a three-dimensional environment that includes one or more physical objects, generate a geometric representation of the scene data, process the scene data using an artificial intelligence machine learning model that outputs object boundary data and object labels, augment the geometric representation with the object boundary data and the object labels, and identify the one or more physical objects based on the augmented geometric representation of the three-dimensional environment. For each identified physical object, the processor is configured to generate an associated virtual object that is fit to one or more geometric characteristics of that identified physical object. The processor is further configured to track each identified physical object and associated virtual object across successive updates to the scene data.

Provided in the embodiments of the disclosure are a method and an apparatus for processing data, an electronic device and a storage medium. The method for processing data includes: obtaining a framework of a target according to a two-dimensional (2D) image; determining an x.sup.th distance from an x.sup.th pixel in the 2D image to the framework; and determining, according to the x.sup.th distance, whether the x.sup.th pixel is a pixel forming the target.

An image processing apparatus comprises processing circuitry configured to: acquire first image data that is representative of a subject at a first time and second image data that is representative of the subject at a second, different time; process the first image data and second image data to obtain a plurality of transformed first data sets and a plurality of transformed second data sets; transform the transformed first data sets and transformed second data sets to obtain respective first distance transforms and second distance transforms; select a combination of at least one of the first distance transforms and at least one of the second distance transforms; generate at least one morphed distance transform based on the combination; and process the at least one morphed distance transform to obtain upsampled image data that is representative of the subject at a third time.

An exemplary system, method, and computer-accessible medium for generating an image(s) of an anatomical structure(s) in a biological sample(s) can include receiving first wide field microscopy imaging information for the biological sample, generating second imaging information by applying a gradient-based distance transform to the first imaging information, and generating the image(s) based on the second imaging information. The second imaging information can be generated by applying an anisotropic diffusion procedure to the first imaging information. The second imaging information can be generated by applying a curvilinear filter and a Hessian-based enhancement filter after the application of the gradient-based distance transform. The second information can be generated by applying (i) a tube enhancement procedure or (ii) a plate enhancement procedure after the application of the gradient-based distance transform.

An image processing apparatus comprises processing circuitry configured to: acquire first image data that is representative of a subject at a first time and second image data that is representative of the subject at a second, different time; process the first image data and second image data to obtain a plurality of transformed first data sets and a plurality of transformed second data sets; transform the transformed first data sets and transformed second data sets to obtain respective first distance transforms and second distance transforms; select a combination of at least one of the first distance transforms and at least one of the second distance transforms; generate at least one morphed distance transform based on the combination; and process the at least one morphed distance transform to obtain upsampled image data that is representative of the subject at a third time.

The invention belongs to the technical field of the quantitative statistical distribution analysis of the features from characteristic images of microstructures and precipitated phases in metal materials, and relates to a quantitative statistical distribution characterization method of precipitate particles with the full field of view in a metal material. The method comprises the following steps of electrolytic corrosion of a metallic material specimen, automatic collection of characteristic images of microstructure, automatic stitching and fusion of the full-view-field microstructure images, automatic identification and segmentation of the precipitate particles and quantitative distribution characterization of the precipitate particles with the full field of view in a large-range scale. By establishing a mathematic model, the large-range automatic stitching and fusion of the characteristic images of the full-view-field microstructures in a characteristic region and the automatic segmentation and identification of the precipitate particles are realized; and the quantitative statistical distribution characterization information of the full-view-field morphology, quantity, size, distribution and the like of plentiful precipitated phases in a larger range is quickly obtained. The method has the features of being accurate, high-efficiency and informative in quantitative distribution characterization, as well as has much more statistical representativeness compared with conventional single-view-field quantitative image analysis.

A method and a device for the characterization of living specimens from a distance are disclosed. The method comprises: acquiring an image of a living specimen and segmenting the image, providing a segmented image; measuring a distance to several parts of said image, providing several distance measurements, and selecting a subset of those contained in the segmented image. The method also processes the segmented image and the distance measurements referred to different positions contained within the segmented image by characterizing the shape and the depth of the living specimen and by comparing a shape analysis map and a depth profile analysis map. If a result of the comparison is comprised inside a given range, parameters of the living specimen are further determined including posture parameters, location or correction of anatomical reference points and/or body size parameters, and/or a body map of the living specimen is represented.

A method, system and computer programs for computing simultaneous rectilinear paths using medical images are disclosed. The method comprises receiving a 3D medical image comprising voxels representing a volume of an anatomical region of a patient and a preliminary path determined by two points traversing said 3D medical image, wherein said 3D medical image has segmented therein at least one area of interest, the preliminary path comprising a security zone with a given distance; computing a distance map of said area of interest and mapping its voxels to a first value or to a second value depending on a distance threshold, the latter being equal to said given distance of the security zone; selecting the voxels having said second value and projecting them using a frustum that projects the preliminary path onto a single point, to obtain a 2D projected image that includes a plurality of rectilinear paths.