Intelligent Atlas for Automatic Image Analysis of Magnetic Resonance Imaging

Abstract

A non-invasive imaging system, including an imaging scanner suitable to generate an imaging signal from a tissue region of a subject under observation, the tissue region having at least one substructure; a signal processing system in communication with the imaging scanner to receive the imaging signal from the imaging scanner; and a data storage unit in communication with the signal processing system, wherein the data storage unit stores an anatomical atlas comprising data encoding spatial information of the at least one substructure in the tissue region, and a pathological atlas corresponding to an abnormality of the tissue region, wherein the signal processing system is adapted to automatically identify, using the imaging signal, the anatomical atlas, and the pathological atlas, a presence of the abnormality or a precursor abnormality in the subject under observation.

Description

CROSS-REFERENCE OF RELATED APPLICATION[0001]This application claims priority to U.S. Provisional Application No. 61 / 329,857 filed on Apr. 30, 2010, the entire contents of which are hereby incorporated by reference.[0002]The U.S. Government has a paid-up license in this invention and the right in limited circumstances to require the patent owner to license others on reasonable terms as provided for by the terms of Grant No.: R01AG20012 and P41RR15241, awarded by the National Institutes of Health.BACKGROUND[0003]1. Field of Invention[0004]The current invention relates to non-invasive imaging systems and methods, and more particularly to imaging systems and methods that provide computer assisted diagnosis of tissue abnormalities in human and animal subjects.[0005]2. Discussion of Related Art[0006]Conventional radiological diagnosis can be qualitative or subjective. Even though quantitative analyses may significantly improve our ability to detect and characterize abnormalities, currentl...

AI Technical Summary

Problems solved by technology

Even though quantitative analyses may significantly improve our ability to detect and characterize abnormalities, currently almost no quantitative techniques can be accepted as a part of routine radiological diagnosis.

This is partly due to difficulties in analyzing tissue based on radiological, such as Magnetic Resonance (MR) images.

For example, high quality segmentation of the brain boundary requires a considerable amount of manual labor, whic

Images