S-MODALS neural network query of medical and forensic imagery databases

Timothy G. Rainey; Dean W. Brettle; Andrew Lavin; Fred Weingard; Claudia Henschke; Dave Yankelevitz; Ion Mateescu; Lee A. Uvanni; Robert W. Sibert; Eric Birnbaum

S-MODALS neural network query of medical and forensic imagery databases

Timothy G. Rainey, Dean W. Brettle, Andrew Lavin, Fred Weingard, Claudia Henschke, Dave Yankelevitz, Ion Mateescu, Lee A. Uvanni, Robert W. Sibert, Eric Birnbaum

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Proceedings of SPIE - The International Society for Optical Engineering
Editors	Peter J. Costianes
Pages	51-61
Number of pages	11
State	Published - 1995
Externally published	Yes
Event	23rd AIPR Workshop: Image and Information Systems: Applications and Opportunities - Washington, DC, USA Duration: 12 Oct 1994 → 14 Oct 1994

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	2368
ISSN (Print)	0277-786X

Conference

Conference	23rd AIPR Workshop: Image and Information Systems: Applications and Opportunities
City	Washington, DC, USA
Period	12/10/94 → 14/10/94

Cite this

Rainey, T. G., Brettle, D. W., Lavin, A., Weingard, F., Henschke, C., Yankelevitz, D., Mateescu, I., Uvanni, L. A., Sibert, R. W., & Birnbaum, E. (1995). S-MODALS neural network query of medical and forensic imagery databases. In P. J. Costianes (Ed.), Proceedings of SPIE - The International Society for Optical Engineering (pp. 51-61). (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 2368).

@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",

}

Rainey, TG, Brettle, DW, Lavin, A, Weingard, F, Henschke, C, Yankelevitz, D, Mateescu, I, Uvanni, LA, Sibert, RW & Birnbaum, E 1995, S-MODALS neural network query of medical and forensic imagery databases. in PJ Costianes (ed.), Proceedings of SPIE - The International Society for Optical Engineering. Proceedings of SPIE - The International Society for Optical Engineering, vol. 2368, pp. 51-61, 23rd AIPR Workshop: Image and Information Systems: Applications and Opportunities, Washington, DC, USA, 12/10/94.

S-MODALS neural network query of medical and forensic imagery databases. / Rainey, Timothy G.; Brettle, Dean W.; Lavin, Andrew et al.
Proceedings of SPIE - The International Society for Optical Engineering. ed. / Peter J. Costianes. 1995. p. 51-61 (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 2368).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - S-MODALS neural network query of medical and forensic imagery databases

AU - Rainey, Timothy G.

AU - Brettle, Dean W.

AU - Lavin, Andrew

AU - Weingard, Fred

AU - Henschke, Claudia

AU - Yankelevitz, Dave

AU - Mateescu, Ion

AU - Uvanni, Lee A.

AU - Sibert, Robert W.

AU - Birnbaum, Eric

PY - 1995

Y1 - 1995

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/0029214914

M3 - Conference contribution

AN - SCOPUS:0029214914

SN - 0819417106

SN - 9780819417107

T3 - Proceedings of SPIE - The International Society for Optical Engineering

SP - 51

EP - 61

BT - Proceedings of SPIE - The International Society for Optical Engineering

A2 - Costianes, Peter J.

T2 - 23rd AIPR Workshop: Image and Information Systems: Applications and Opportunities

Y2 - 12 October 1994 through 14 October 1994

ER -

S-MODALS neural network query of medical and forensic imagery databases

Abstract

Publication series

Conference

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