Targeting breast cancer detection with military technology

IEEE Engineering in Medicine and Biology Magazine

Volumn 21, Issue 6, 2002, Pages 36-40

  Irvine, John M ^a  

^a SCIENCE APPLICATIONS INTERNATIONAL CORPORATION   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARMY; AUTOMATION; BREAST CARCINOMA; CANCER DIAGNOSIS; CANCER SCREENING; COST EFFECTIVENESS ANALYSIS; DECISION MAKING; GOVERNMENT; HUMAN; INFORMATION PROCESSING; MEDICAL TECHNOLOGY; REVIEW; SENSOR;

ALGORITHMS; BREAST NEOPLASMS; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFRARED RAYS; MILITARY SCIENCE; PATTERN RECOGNITION, AUTOMATED; QUALITY CONTROL; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE; TECHNOLOGY TRANSFER; UNITED STATES;

EID: 0036880486     PISSN: 07395175     EISSN: None     Source Type: Journal    
DOI: 10.1109/MEMB.2002.1175136     Document Type: Review

References (17)

1. E. Agassi and N. Ben Yosef, "The effect of the thermal infrared data on principal component analysis of multi-spectral remotely-sensed data," Int. J. Remote Sens., vol. 19, no. 9, pp. 1683-1694, 1998.
2. A.P. Bowman, W.M. Winter, A.D. Stocker, and P.G. Lucey, "Hyperspectral infrared techniques for buried landmine detection," in Proc. 4th Int. Airborne Remote Sensing Conf., Ottawa, Canada, 21-24 June 1999, vol. 1, pp. I-19-I-26.
3. A.P. Bowman, E.M. Winter, A.D. Stocker, and P.G. Lucey, "Hyperspectral infrared techniques for buried landmine detection," in Proc. Detection of Abandon Land Mines Conf., Edinburgh, Scotland, 12-14 Oct. 1998, pp. 129-133.
4. R.R. Brooks and S.S. Iyengar, Multi-Sensor Fusion: Fundamentals and Applications with Software. Englewood Cliffs, NJ: Prentice-Hall, 1997.
5. D.E. Dudgeon and R.T. Lacoss, "An overview of automatic target recognition," MIT Lincoln Lab. J., vol. 6, no. 1, pp. 2-10, spring 1993.
6. B. Eckstein and J.M. Irvine, "Evaluating the benefits of assisted target recognition," in Proc. 30th Appl. Imagery and Pattern Recognition Workshop, Washington, DC, 10-12 Oct. 2001, pp, 39-45.
7. J.P. Egan, Signal Detection Theory and ROC Analysis. New York: Academic, 1975.
8. D.B. Green and J.A. Swets, Signal Detection Theory and Psychophysics. New York: Wiley, 1966.
9. D.L. Hall, Mathematical Techniques in Multisensor Data Fusion. Norwood, MA: Artech House, 1992.
10. L.A. Klein, Sensor and Data Fusion Concepts and Applications, 2nd ed. Bellingham, WA: SPIE Optical Engineering Press, 1999.
11. J.M. Irvine, "Evaluating assisted target recognition performance: An assessment of DARPA's SAIP system," in Proc. SPIE AeroSense, Orlando, FL, 5-9 Apr. 1999, pp. 694-704.
12. J.M. Irvine, A.P. Bowman, E. Rosenfeld, R. Meyer, S. Israel, A. Stocker, E. Ensafi, and G. Maksymonko, "Analysis of airborne LWIR hyperspectral data for buried landmine detection," presented at the UXO/Countermine Forum 2000, Anaheim, CA, 3 May 2000.
13. J.C. Mossing and T.D. Ross, "An evaluation of SAR ATR algorithm performance sensitivity to MSTAR extended operating conditions," in SPIE Aerosense, Apr. 1998, vol. 3370, no. 54.
14. L.M. Novak, G.R. Benitz, G.J. Owirka, and J.D. Popielarz, "Classifier performance using enhanced resolution SAR data," in Proc. Radar 97, Lexington, MA, 14-16 Oct. 1997, pp. 634-638.
15. J.C. Ogilvie and C.D. Creelman, "Maximum likelihood estimation of ROC curve parameters," J. Math. Psych., vol. 5, pp. 377-391, 1968.
16. T.D, Ross and J.C. Mossing, "The MSTAR evaluation methodology," in Proc. SPIE Conf. Algorithms for Synthetic Aperture Radar Imagery VI, Orlando, FL, Apr. 1999.
17. L. Westerkamp, et al., "Problem set guidelines to facilitate ATR research, development, and performance assessments," in SPIE AeroSense 2002, Orlando, FL, 1-5 Apr. 2002.