Fujifilm Corporation

Voxeleron, LLC

Other

Johns Hopkins University

Daniel Benjamin Russakoff

Jonathan David Oakley

Chao Shi

Huzefa Neemuchwala

Akira Hasegawa

Jonathan Oakley

Seungseok Oh

Joseph L Mankowski

Methods are disclosed for the generation and editing of layer delineations within three-dimensional tomography scans. Cross sections of a subject are generated and presented to an operator, who has the ability to edit layer delineations within the cross section, or determine parameters used to generate new cross sections. By guiding an operator through a set of displayed cross sections, the methods can allow for a more rapid, efficient, and error-free segmentation of the subject. The cross sections can be nonplanar in shape or planar and non-axis-aligned. The cross sections can be restricted to exclude one or more user-defined regions of the subject, or to include only one or more user-defined regions of the subject. The cross sections can be localized to a point-of-interest. Iterative implementations of the methods can be used to arrive at a segmentation deemed satisfactory by the user.

Method and apparatus for generation or editing of layer delineations

The present invention is directed to a software algorithm that measures the number of corneal nerve fibers in images captured by microscopy including images from patients obtained by in vivo corneal confocal microscopy, a noninvasive technique. The present invention solves a complicated segmentation problem, by exploiting the piece wise linear nature of the nerve fibers&#x2014;i.e., the nerves are made up of a lot of straight line segments. The image is split into sub-regions, where each sub-region contains nerves mostly running in the same, straight direction. Having the nerves all in straight-lines within a single 2d image region dramatically simplifies the segmentation problem. The image intensities are summed in the direction of the nerves to reduce the 2d representation to a 1d signal having pronounced peaks where the nerves are located.

Automated methods to count corneal subbasal nerves

A method is provided that includes identifying a plurality of data sets, each data set is associated with a distribution model and each data set is associated with an image having a first noise level. The method includes partitioning the data sets into a plurality of groups and generating a best representative estimate for each group, the estimate is associated with a second noise level that is less than the first noise level. The method further includes annotating each group and receiving an input data set. The method includes assigning the input data set to a group and annotating the input data set according to that group's annotation.

Method and system for image analysis and interpretation

A system and method are provided for model-based coronary artery calcium (CAC) scoring. A model image of a heart region is aligned with an image of a patient's heart region in order to more easily identify the coronary arteries and other relevant anatomical features in the image. Once the images are aligned, relevant calcium plaques are identified by their presence within a coronary artery, and the relevant plaques are then labeled by the specific coronary artery in which they are located. The coronary arteries with the labeled plaques are scored individually based on their size and X-ray attenuation, and an overall score based on all of the relevant plaques is then computed, which is related to the patient's risk for coronary artery disease.

Model-based coronary artery calcium scoring

Methods and apparatuses process images. The method according to one embodiment accesses digital image data representing an image including an object; accesses reference data including a shape model relating to shape variation of objects from a baseline object, the objects and the baseline object being from a class of the object; and removes from the image an element not related to the object, by representing a shape of the object using the shape model.

Method and apparatus of using probabilistic atlas for feature removal/positioning

A method and an apparatus for automatic segmentation of an image representing a mass of a tissue region based on dynamic programming that guarantees an accurate and closed contour of the mass is disclosed. The method according to one embodiment accesses digital image data representing an image including the mass of the tissue region, creates a mirror image of the digital image data, extracts a Region of Interest (ROI) which includes a portion of the mirror image containing the mass, transforms the ROI to polar space for obtaining a polar image of the ROI, assigns local cost to sub portions of the polar image, and finds a contour of the mass based on the assigned local cost.

Mass segmentation using mirror image of region of interest

Methods and an apparatus process images. The method according to one embodiment accesses digital image data representing a plurality of objects with a plurality of features; generates a shape model for shapes of the plurality of objects, the step of generating a shape model including generating a baseline object by aligning the plurality of objects, and determining deformation modes to describe shape deformations between shapes of the plurality of objects and the baseline object; performs shape registration for the plurality of objects by fitting shapes of the plurality of objects using combinations of the deformation modes, to obtain registered shapes; and generates a probabilistic atlas by mapping the plurality of features from the plurality of objects to the baseline object, using the registered shapes for the plurality of objects.

Method and apparatus for probabilistic atlas based on shape modeling technique

A method and an apparatus process images. The method according to one embodiment accesses digital image data representing an image including an object; clusters pixels of the image to obtain clusters; generates a graph with pixels of the image and cluster membership information of pixels in the clusters; and segments the graph using a max-flow segmentation to obtain pixels of the image associated with the object.

Method and apparatus for detection using cluster-modified graph cuts

Methods and apparatuses detect features. The method according to one embodiment accesses digital image data representing an object; accesses reference data including a shape model relating to shape variation from a baseline object, and a probabilistic atlas comprising probability for a feature in the baseline object; performs shape registration for the object by representing a shape of the object using the shape model, to obtain a registered shape; and determines probability for the feature in the object by generating a correspondence between a geometric element associated with the probabilistic atlas and a geometric element associated with the registered shape.

Method and apparatus of using probabilistic atlas for cancer detection

A method and an apparatus process images. The method according to one embodiment accesses digital image data including a region of interest; and calculates a Hessian peak characteristic for the region of interest, the calculating step including summing eigenvalues of a Hessian matrix to obtain the Hessian peak characteristic, wherein the Hessian matrix is associated with a pixel property in the region of interest.

Method and apparatus for candidate detection using Hessian peak characteristics

Methods and apparatuses process images. The method according to one embodiment accesses digital image data representing an image including an object; generates a connected graph associated with the image, the generating step including representing pixels of the image in a higher than two dimensional space to obtain pixel representations, generating a pixel representation graph using the pixel representations, and assigning weights to edges between the pixel representations in the pixel representation graph, based on a gradient characteristic between the pixel representations, to obtain a connected graph; and segments the connected graph using an energy minimizing function, to obtain pixels of the image associated with the object.

Growing community of inventors

San Francisco, CA, United States of America

Daniel Benjamin Russakoff