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A Fully Automatic System For Verified Computerized Stereoanalysis

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 2R44MH076541-04
Agency Tracking Number: MH076541
Amount: $799,219.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: N/A
Solicitation Number: N/A
Solicitation Year: N/A
Award Year: 2009
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
United States
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 (410) 643-4901
Business Contact
Phone: (410) 643-4901
Research Institution

DESCRIPTION (provided by applicant): A Fully Automatic System For Verified Computerized Stereoanalysis SUMMARY The requirement for a trained user to interact with tissue and images is a long-standing impediment to higher throughput analysis of biological microstructures using unbiased stereology, the state-of-the-art method for accurate quantification of biological structure. Phase 1 studies addressed this limitation with Verified Computerized Stereoanalysis (VCS), an innovative approach for automatic stereological analysis that improves throughput efficiency by 6-9 fold compared to conventional computerized stereology. Work in Phase 2 integrated VCS into the Stereologer , an integrated hardware-software-microscopy system for stereological analysis of tissue sections and stored images. Validation studies of first-order stereological parameters. i.e., volume, surface area, length, number, confirmed that the color-based detection methods in the VCS approach achieve accurate results for automatic stereological analysis of high S:N biological microstructures. These studies indicate that fully automatic stereological analysis of tissue sections and stored images can be realized by elimination of two remaining barriers, which will be addressed in this Phase II Continuation Competing Renewal. In Aim 1, applications for feature extraction and microstructure classification, developed in part with funding from the Office of Naval Research, will be integrated into the VCS program. The new application (VCS II) will use these approaches to automatically detect and classify polymorphic microstructures of biological interest using a range of feature calculations, including size, color, border, shape, and texture, with support from active learning and Support Vector Machines. Work in Aim 2 will eliminate physical handling of glass slides during computerized stereology studies by equipping the Stereologer system with automatic slide loading/unloading technology controlled by the Stereologer system. This technology will approximately double the throughput efficiency of the current VCS program and support human-in-the-loop interaction for sample microstructures on the border between two or more adjacent classes. The studies in Aim 3 will rigorously test the hypothesis that fully automatic VCS can quantify first- and second-order stereological parameters, without a loss of accuracy compared to the current gold-standard - non-automatic computerized stereology, e.g., manual Stereologer. If these studies validate the accuracy of VCS II, then commercialization of the fully automatic program will facilitate the throughout efficiency for testing scientific hypotheses in a wide variety of biomedical research projects; reduce labor costs for computerized stereology studies; hasten the growth of our understanding of biological processes that underlie health, longevity, and disease; and accelerate the development of novel approaches for the therapeutic management of human disease. Solid evidence that the SRC and its strategic partners can effectively commercialize this technology is demonstrated by their worldwide sales and support of the Stereologer system for the past 13 years. Key personnel and participating institutions: 7 Peter R. Mouton, Ph.D. (PI), Stereology Resource Center, Chester, MD. 7 Dmitry Goldgof, Ph.D., University of South Florida Coll. Engineering, Tampa, Fl. 7 Larry Hall, Ph.D., University of South Florida Coll. Engineering, Tampa, Fl. 7 Joel Durgavich, MS, Systems Planning and Analysis, Alexandria, VA. 7 Kurt Kramer, MS, Computer Programmer, University of South Florida, Coll. Engineering, Tampa, Fl. 7 Michael E. Calhoun, Ph.D., Sinq Systems, Columbia, MD PUBLIC HEALTH RELEVANCE: Many fields of scientific research require a trained expert to make tedious and repetitive measurements of microscopic changes in animal and human tissues. This project will produce a computer program that performs these measurements with equal accuracy to a trained expert, but with dramatic savings in time and costs. Allowing scientists to complete more research in less time will accelerate our understanding of the factors that promote health and longevity, and hasten progress toward the development of new treatments for human diseases.

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

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