To See is to Believe: Looking at the Scars of Subsurface Digital Imaging

Gabriel Thomas, University of Manitoba

Abstract

Technology has accomplished goals that seemed once impossible such as flying and planetary exploration. Subsurface imaging is one of these accomplishments that during the years has seen many variations of techniques and approaches proposed for a wide variety of applications ranging from breast cancer detection [1,2] to seismographic exploration [3]. Sound, microwave energy, x-rays are but a few of the modalities that allow us to see the structure of subsurface information. While, for example, the ability to look at the body inner organs through the use of magnetic resonance imaging [4] is an extraordinary accomplishment, subsurface imaging usually deals with very low signal to noise ratios [5] and insufficient resolution that makes the detection of targets extremely difficult.

This presentation discusses the difficulties encountered when using microwave imaging systems and MRI for subsurface imaging and segmentation. Emphasis is placed on the importance of obtaining focused high-resolution images for further automatic detection and classification. Research and results regarding buried plastic landmine detection, microwave breast imaging and automatic segmentation of MRI imagery will be presented. In such difficult scenarios, incorporating ideas from other fields (such as knowledge based systems) can accomplish reliable automatic target recognition.

References

[1] E. C. Fear and M. A. Stuchly, "Microwave detection of breast cancer," IEEE Trans. Microwave Theory and Techniques, vol. 48, pp. 1854 - 1863, Nov. 2000.
[2] S. C. Hagness, A. Taflove, and J. E. Bridges "Three dimensional FDTD analysis of a pulsed microwave confocal system for breast cancer detection: Design of an antenna-array element" IEEE Trans. Ant. and Prop., vol. 47, pp. 783-791, May 1999.
[3] G. F. Margrave, "Numerical Methods of Exploration Seismology with Algorithms in MATLAB," M. Sc. Thesis, Department of Geology and Geophysics, The University of Calgary, Canada, 2001.
[4] Z. Pei-Liang, P.C. Lauterbur, Principles of Magnetic Resonance Imaging: A Signal Processing Perspective. New York, NY: IEEE Press, 2000.
[5] D. J. Daniels, Ground Penetrating Radar. London, UK: IEE Press, 2004.