Johns Hopkins University

David W Porter

William C Walton

Brett D Lapin

Benjamin M W Tsui

Susan C Harvey

Keith S Peyton

A method for characterizing and locating abnormal tissue in an area of interest in a body is provided. The method may include receiving first and second modality examination data including a plurality of first and second modality examination data segments of the area of interest and determining, by evaluating each first and second modality examination data segment, a set of modality detection candidates based on the first and second modality examination data and a first and second modality feature likelihood model. The method may also include generating a modal or multi-modal correspondence anatomic model of the area of interest by registering the plurality of first and second modality examination data segments, determining one or more modal abnormal tissue detections by fusing the set of modality detection candidates using the modal or multimodal correspondence anatomic model, and providing a modal diagnosis confidence score and a modal anatomic location based on the one or more modal abnormal tissue detections.

Abnormal tissue detection via modal upstream data fusion

The present invention provides systems and methods for automatically mining massive intelligence databases to discover sequential patterns therein using a novel combination of forward and reverse temporal processing techniques as an enhancement to well known pattern discovery algorithms.

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Centerville, MD, United States of America

David W Porter