Leland Stanford Junior University

General Electric Company

Christopher Allen Beaulieu

David Seungwon Paik

Sandy A Napel

Burak Acar

Prakash Mahesh

Denny Wingchung Lau

Steven P Roehm

Vijaykalyan Yeluri

Sandip Biswal

Garry Evan Gold

Robert John Herfkens

R Brooke Jeffrey, Jr

Salih Burak Gokturk

Carlo Tomasi

Geoffrey D Rubin

Padmavathi Sundaram

Ender Konukoglu

Certain embodiments of the present invention provide methods and systems for synchronizing a view of a patient image with an atlas image. Certain embodiments provide a method for synchronizing a patient image with an atlas image. The method includes retrieving an image atlas including at least one atlas image, registering an atlas image to a patient image and synchronizing a view of the atlas image to a view of the patient image. In certain embodiments, the method further includes registering a plurality of atlas images to a plurality of patient images. In certain embodiments, the step of synchronizing further includes synchronizing at least one of orientation, zoom level, window level and pan of the atlas image to the patient image.

Systems and methods for synchronized image viewing with an image atlas

A method for detecting and identifying structures of interest such as colonic polyps or similar structures like lung nodules in volumetric (medical) images data is provided. The method includes obtaining a heat diffusion field (HDF) by applying a heat diffusion scheme to a volume of interest that includes structures. The obtained heat diffusion field is then used for identifying a structure of interest from the structures in the volume of interest using a geometrical analysis of the heat diffusion field. The heat diffusion scheme is, at least partly, governed by non-linear diffusion parameters. The identification includes two parts: (i) the computation of a spherical symmetry parameter, and (ii) the performance of a local analysis of the volume of interest and computation of a triangulization parameter.

Heat diffusion based detection of structures of interest in medical images

A method of identifying polyps and in a medical image is provided. In a first step, a 3-dimensional model is made of the medical image that contains both polyps (if any were present in the original medical image) and folds. Next, a second 3-dimensional model of the medical image, which is a filtered version of the first model, is constructed in which folds are preserved, but polyps are minimized or eliminated. In a third step, any polyps that were contained in the medical image are identified by subtracting the second 3-dimensional model from the first 3-dimensional model. This subtraction results in a third 3-dimensional model, in which polyps are preserved but folds are minimized or eliminated. With the present inventive method, polyps may be easily and quickly identified without interference from folds.

Polyp identification through subtraction of models of medical images

A method to detect and classify a structure of interest in a medical image is provided to enable high specificity without sacrificing the sensitivity of detection. The method is based on representing changes in three-dimensional image data with a vector field, characterizing the topology of this vector field and using the characterized topology of the vector field for classification of a structure of interest. The method could be used as a stand-alone method or as a post-processing method to enhance and classify outputs of a high-sensitivity low-specificity method to eliminate false positives.

Method for detecting and classifying a structure of interest in medical images

An automatic method for the registration of prone and supine computed tomographic colonography data is provided. The method improves the radiologist's overall interpretation efficiency as well as provides a basis for combining supine/prone computer-aided detection results automatically. The method includes determining (centralized) paths or axes of the colon from which relatively stationary points of the colon are matched for both supine and prone positions. Stretching and/or shrinking of either the supine or prone path perform registration of these points. The matching and registration occurs in an iterative and recursive manner and is considered finished based on one or more decision criteria.

Method for matching and registering medical image data

A computer-implemented method for determining and characterizing, which portions or shapes of a medical image correspond to a shape of interest is provided. A candidate shape is obtained after which a visible surface is computed adjacent to this candidate shape. A visible surface includes one or more portions of the medical image that are visible by the candidate shape. Once the visible surface is determined, parameters of the visible surface are computed. Then the method further includes the step of determining whether the candidate shape corresponds to a shape of interest. The method further includes the step of computing features of the candidate shape and/or classifying the candidate shape. The advantage of the computer-implemented method is that it provides a high detection specificity, i.e. reducing false positives, without sacrificing sensitivity of the detection of a shape of interest.

Method for characterizing shapes in medical images

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Los Altos, CA, United States of America

Christopher Allen Beaulieu