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Enhanced Software Tools for Detecting Anatomical Differences in Image Data Sets

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R41MH118845-01
Agency Tracking Number: R41MH118845
Amount: $694,622.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: 105
Solicitation Number: PA18-591
Timeline
Solicitation Year: 2018
Award Year: 2018
Award Start Date (Proposal Award Date): 2018-09-18
Award End Date (Contract End Date): 2020-08-31
Small Business Information
28 CORPORATE DR
Clifton Park, NY 12065-8688
United States
DUNS: 010926207
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 SAMUEL GERBER
 (518) 371-3971
 samuel.gerber@kitware.com
Business Contact
 WILLIAM SCHROEDER
Phone: (518) 371-3971
Email: will.schroeder@kitware.com
Research Institution
 WASHINGTON UNIVERSITY
 
CAMPUS BOX 1054
SAINT LOUIS, MO 63130-4862
United States

 Nonprofit College or University
Abstract

Project Summary Morphometric analysis is a primary algorithmic tool to discover disease and drug related effects on brain anatomy. Neurological degeneration and disease manifest in subtle and varied changes in brain anatomy that can be non-local in nature and effect amounts of white and gray matter as well as relative positioning and shapes of local brain anatomy. State-of-the-art morphometry methods focus on local matter distribution or on shape variations of apriori selected anatomies but have difficulty in detecting global or regional deterioration of matter; an important effect in many neurodegenerative processes. The proposal team recently developed a morphometric analysis based on unbalanced optimal transport, called UTM, that promises to be capable to discover local and global alteration of matter without the need to apriori select an anatomical region of interest. The goal of this proposal is to develop the UTM technology into a software tool for automated high-throughput screening of large neurological image data sets. A more sensitive automated morphometric analysis tool will help researchers to discover neurological effects related to disease and lead to more efficient screening for drug related effects.Project Narrative Describing anatomical differences in neurological image data set is a key technology to non-invasively discover the effects of disease processes or drug treatments on brain anatomy. Current morphometric analysis focus on local matter composition and on the shape of a priori defined regions of interest. The goal of this proposal is to extend the capabilities of image based morphometric analysis to be able to discover regionally varying deterioration and alteration of matter without the need for fine-grained segmentations and a priori definitions of regions of interest.

* Information listed above is at the time of submission. *

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