<title>S-MODALS neural network query of medical and forensic imagery databases</title>

Abstract

A dual-use neural network technology, called the statistical-multiple object detection and location system (S-MODALS), has been developed by Booz(DOT)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.

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