A computer implemented method for performing bone segmentation in imaging data of a section of a body structure is provided. The method includes: Obtaining the imaging data including a plurality of 2D images of the section of the body structure; and performing a multiphase local-based hybrid level set segmentation on at least a subset of the plurality of 2D images by minimizing an energy functional including a local-based edge term and a local-based region term computed locally inside a local neighborhood centered at each pixel of each one of the 2D images on which the multiphase local-based hybrid level set segmentation is performed, the local neighborhood being defined by a Gaussian kernel whose size is determined by a scale parameter (σ).

Embodiments of the present invention provide systems, methods, and computer storage media directed to operations to facilitate real-time matting using local color estimation and propagation. In accordance with embodiments described herein, an unknown region is estimated based on a set of received boundary points (a zero-level contour that separates the foreground object from the background) and additional contours based on increasing distances from the zero-level contour. The background and foreground colors for each pixel in the unknown region can be estimated and utilized to propagate the foreground and background colors to the appropriate contours in the unknown region. The estimated background and foreground colors may also be utilized to determine the opacity and true background and foreground colors for each pixel in the unknown region which results in an image matted in real-time.

A method and apparatus for segmenting an object from a three-dimensional image are disclosed. According to the method, first, a surface of the object is estimated using scale estimation processes such as Laplacian-of-Gaussian filters in one, two or three dimensions. Second, the estimated surface is transformed by having a shrink function applied to it independently in each dimension to give a regularly shaped (preferably substantially spherical), non-isotropic shape. The object is segmented from the volume around it, and is inverse-transformed to obtain the original shape, which shape is then isolated from the image volume.

A method of image-based quantification for allergen skin reaction includes imaging an area of skin that has been subject to a skin-prick test to produce one or more images of the area. The method includes identifying regions of wheal and/or flare in the one or more images of the area and quantifying weal and/or flare indicators based on the regions identified. The method also includes outputting results of the quantified wheal and/or flare indicators indicative of quantified allergen skin reaction.

A system includes a sensor and a tracking subsystem. The tracking subsystem receives an image feed of top-view images generated by the sensor. The tracking subsystem detects an event associated with an item being removed from a rack. The tracking subsystem determines that a first person and a second person may be associated with the event. In response, the tracking subsystem dilates contours associated with the first and second person from a first depth to a second depth until the contours enter a zone adjacent to the rack. A number of iterations is determined for each contour to enter the zone adjacent to the rack. If the first person's contour enters the zone in fewer iterations, the item is assigned to the first person.

A method for determining a contour of the representation, on a photo of an object made up of one or several elements, referred to as an “actual contour.” The method includes the following steps: 1) application of a first treatment to the photo so as to obtain a first image representing a first contour of the object; 2) application of a second treatment to the photo so as to obtain a second image representing a second contour of the object; 3) association, according to a predetermined association algorithm, of each point of the second contour with a point of the first respective contour, then removal of the points of the first contour that have not been associated with a point of the second contour, the first image then representing a corrected contour of the object.

A method and computer-based system is provided that assists physicians in detecting early tumor growth and allowing modification of treatment to have a positive impact on medical management, patient morbidity, outcomes and survival times. The method comprises measuring tumor volumes from radiological images to predict growth by a statistical method. The methods allow detection of increases in tumor size earlier than is currently possible and, therefore, advantageous in modifying or optimizing treatment.

A method and apparatus of detection, registration and quantification of an image is described. The method may include obtaining an image of a lithographically created structure, and applying a level set method to an object, representing the structure, of the image to create a mathematical representation of the structure. The method may include obtaining a first dataset representative of a reference image object of a structure at a nominal condition of a parameter, and obtaining second dataset representative of a template image object of the structure at a non-nominal condition of the parameter. The method may further include obtaining a deformation field representative of changes between the first dataset and the second dataset. The deformation field may be generated by transforming the second dataset to project the template image object onto the reference image object. A dependence relationship between the deformation field and change in the parameter may be obtained.

Systems and methods for managing motions of an anatomical region of interest of a patient during image-guided radiotherapy are disclosed. An exemplary system may include an image acquisition device, a radiotherapy device, and a processor device. The processor device may be configured to control the image acquisition device to acquire at least one 2D image. Each 2D image may include a cross-sectional image of the anatomical region of interest. The processor device may also be configured to perform automatic contouring in each 2D image to extract a set of contour elements segmenting the cross-sectional image of the anatomical region of interest in that 2D image. The processor device may be further configured to match the set of contour elements to a 3D surface image of the anatomical region of interest to determine a motion of the anatomical region of interest and to control radiation delivery based on the determined motion.

The present disclosure may provide a method for segmenting an image. The method may include obtaining an image and related information. The image may include a tumor region. The method may also include determining a region of interest in the image. The region of interest may include the tumor region. The method may also include performing a first segmentation of the region of interest to obtain a first segmentation result. The first segmentation may include: determining tumor morphology relating to the tumor region; performing a second segmentation of the region of interest to obtain a second segmentation result; and optimizing, based on the tumor morphology, the second segmentation result to obtain the first segmentation result.