General Electric Company

The Brigham and Women's Hospital, Inc.

Other

Wisconsin Alumni Research Foundation

University of Pennsylvania

Mitsubishi Electric Information Technology Center America, Inc (ita)

Ron Kikinis

William E Lorensen

Carl-Fredrik Westin

Harvey E Cline

Charles L Dumoulin

Robert David Darrow

Takeo Kanade

Christopher Allen Nafis

Ferenc A Jolesz

Timothy Patrick Kelliher

Sarah F Gibson

Allen Robert Tannenbaum

George R Washko

Jeffrey W Berger

William M Wells, Iii

Raúl San José Estépar

W Eric L Grimson

Steven Haker

John J Reilly

Sigurd B Angenent

William Eric Grimson

David Egidio Altobelli

Renaud Keriven

Michael E Leventon

Olivier Faugeras

Edwin K Silverman

Liana M Lorigo

A method for reconstructing an image includes receiving tomographic data representative of an image signal; deriving, from the image signal, a plurality of components; identifying a spatial location associated with maximum phase congruency of the components; incorporating, into an image, an edge at the spatial location; and providing an output representative of the image.

Measurement of thin-layered structures in X-ray computer tomography

MRA segmentation using active contour models

A computerized apparatus and associated method and program code on a storage medium, for producing a flattening map of a digitized image. This image may be initially synthetically produced as discrete data or as quasi-discrete image data of a real object&mdash;and the original image data may be stored as two-, three-, or four-dimensional dynamic coordinate data. Once produced, the flattening map can be conformally mapped onto the computer generated surface (whether 2-D, 3-D, or any of the dynamically-varying family of surfaces) for display on a computer-assisted display apparatus in communication with a processor. The apparatus and associated method and program code include constructing a first set of data comprising a plurality of discrete surface-elements to represent at least a portion of a surface of the digitized image, and performing a flattening function on the first set of data to produce the flattening map. The flattening function includes computing, for each discrete surface-element, a solution to each of two systems of linear equations formulated from finding a numerical solution to a selected partial differential equation (PDE), and can be performed on each of a series of data sets changing over time to produce a corresponding series of flattening maps.

Apparatus for producing a flattening map of a digitized image for conformally mapping onto a surface and associated method

A patient simulation includes a patient generator for providing an image of a body of a patient on a display, where at least one portion of the body an be examined in greater detail; at least one communication device for allowing interaction between the patient and a user; and a behavior generator which causes the patient to appear to respond to treatment. The behavior generator includes psychological state data that allows the patient to react to the user's 'bedside manner.' Further, the simulation operates on a non-stop basis and in real time.

Personal patient simulation

An ophthalmic augmented reality environment is developed in order to allow for (a) more precise laser treatment for ophthalmic diseases, (b) teaching, (c) telemedicine, and (d) real-time image measurement, analysis, and comparison. A preferred embodiment of the system is designed around a standard slit-lamp biomicroscope. The microscope is interfaced to a CCD camera, and the image is sent to a video capture board. A single computer workstation coordinates image capture, registration, and display. The captured image is registered with previously stored, montaged photographic and/or angiographic data, with superposition facilitated by fundus-landmark-based fast registration algorithms. The computer then drives a high intensity, VGA resolution video display with adjustable brightness and contrast attached to one of the oculars of the slit-lamp biomicroscope.

Technique for creating an ophthalmic augmented reality environment

An interactive surgery planning and display system mixes live video of external surfaces of the patient with interactive computer generated models of internal anatomy obtained from medical diagnostic imaging data of the patient. The computer images and the live video are coordinated and displayed to a surgeon in real-time during surgery allowing the surgeon to view internal and external structures and the relation between them simultaneously, and adjust his surgery accordingly. In an alternative embodiment, a normal anatomical model is also displayed as a guide in reconstructive surgery. Another embodiment employs three-dimensional viewing.

Computer graphic and live video system for enhancing visualization of

A virtual internal cavity inspection system non-invasively provides images of cavities of a subject from a viewpoint within the cavity. An acquisition unit acquires imaging information about internal structures of a subject. This imaging information is segmented into separate structures, and a 3D surface model is constructed. An operator views an image of the 3D model to select a goal viewpoint and a start viewpoint. A viewpoint path is created linking the start viewpoint and the goal viewpoint. Images are created with a viewpoints along the viewpoint path. A variety of additional visualization techniques aid the viewer's localization of the current image viewpoint, and its relation to the subject.

Virtual internal cavity inspection system

A statistical method for correcting for intensity inhomogeneities in the images produced by magnetic resonance imaging equipment. The method uses knowledge of tissue properties and gain inhomogeneities to correct the gain artifact, thereby improving intensity-based segmentation of the volume spanned by the imagery into the various tissue types that are present. The method utilizes the Expectation-Maximization algorithm to simultaneously estimate tissue class and the radiofrequency gain field. The algorithm iterates two components to convergence: tissue classification and gain field estimation. The method combines them in an iterative scheme that yields a powerful technique for estimating tissue class and radiofrequency gain.

Correction of magnetic resonance imager intensity inhomogeneities using

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Brookline, MA, United States of America

Ron Kikinis