@inproceedings{85a90a5e81d14c2392ffa2b019657038,
title = "S-MODALS neural network query of medical and forensic imagery databases",
abstract = "A dual-use neural network technology, called the statistical-multiple object detection and location system (S-MODALS), has been developed by Booz·Allen \& Hamilton, Inc. over a five year period, funded by various U.S. Air Force organizations for automatic target recognition (ATR). S-MODALS performs multi-sensor fusion (Visible(EO), IR, ASARS) and multi-look evidence accrual for tactical and strategic reconnaissance. This paper presents the promising findings of applying S-MODALS to the medical field of lung cancer and the S- MODALS investigation into the intelligent database query of the FBI's ballistic forensic imagery. Since S-MODALS is a learning system, it is readily adaptable to object recognition problems other than ATR as evidenced by this joint government-academia-industry investigation into the S-MODALS automated lung nodule detection and characterization of CT imagery. This paper also presents the full results of a FBI test of the S-MODALS neural network's capabilities to perform an intelligent query of the FBI's ballistic forensic imagery.",
author = "Rainey, \{Timothy G.\} and Brettle, \{Dean W.\} and Andrew Lavin and Fred Weingard and Claudia Henschke and Dave Yankelevitz and Ion Mateescu and Uvanni, \{Lee A.\} and Sibert, \{Robert W.\} and Eric Birnbaum",
year = "1995",
language = "English",
isbn = "0819417106",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
pages = "51--61",
editor = "Costianes, \{Peter J.\}",
booktitle = "Proceedings of SPIE - The International Society for Optical Engineering",
note = "23rd AIPR Workshop: Image and Information Systems: Applications and Opportunities ; Conference date: 12-10-1994 Through 14-10-1994",
}