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A Unified Discipline of Subsurface Sensing and Imaging Systems

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Abstract

Subsurface sensing and imaging seeks to locate and identify objects or conditions underneath an obscuring media by monitoring a probe or wave outside the surface. Many of the mathematical and physical models used in this process are common to underground and underwater environmental exploration, medical imaging, and three-dimensional microscopies, allowing a common framework of physic-based signal processing (PBSP) to be applied. The basis for a unified discipline of subsurface sensing and imaging can be identified from a few general subsurface information extraction strategies. These strategies and their related families of PBSP algorithms can be used to guide a systems-oriented approach to subsurface solutions.

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References

  1. Strada, G., 1996, Horror of landmines: Scientific American, May, p. 40.

  2. Colton, D., and Kress, R., 1992, Inverse acoustic and electromagnetic scattering theory: Applied Mathematical Science Series, v. 93: Springer-Verlag.

  3. Colton, D., and Monk, P., 1994, The detection and monitoring of leukemia using electromagnetic wavers: Mathematical Theory: Inverse Problems, v. 10, p. 1235–1251.

    Google Scholar 

  4. O'sullivan, J. A., Blute, R. E., and Snyder, D. L., 1998, Information theoretic image formation: IEEE Trans. Information Theory, v. 44, p. 2094–2121.

    Google Scholar 

  5. Denk, W., Strickler, J. H., and Webb, W. W., 1990, Two-photon laser scanning fluorescence microsopy: Science, v. 248, p. 73–76.

    Google Scholar 

  6. Pawley, J. B., ed., 1995, Handbook of biological confocal microscopy: Plenum Press, New York, p. 445–458.

    Google Scholar 

  7. Denk, W., 1996, Two-photon excitation in functional biological imaging: Jour. Biomed. Optics, v. 1, p. 296–304.

    Google Scholar 

  8. Ramachandran, G. N., and Laksshminarayan, A. V., 1971, Three-dimensional reconstructions from radiographs and electron micrographs: Applications of convolution instead of fourier transforms: Proc. Nat. Acad. Sci., USA, v. 68, p. 2236–2240.

    Google Scholar 

  9. Shepp, I. A., and Logan, B. F., 1974, The fourier reconstruction of a head section: IEEE Trans. Nucl. Sci., v. NS-21, p. 21–43.

    Google Scholar 

  10. Wolf, E., 1996, in Consortini, A. ed., Principles and development of diffraction tomography: Trends in optics: Academic Press, San Diego.

    Google Scholar 

  11. Devaney, A. J., 1982, A Altered back-propagation algorithm for diffraction tomography: Ultrasonic Imag., v. 4, p. 336.

    Google Scholar 

  12. Devaney, A. J., 1983, A computer simulation study of diffraction tomography: IEEE Trans. on Biomed. Eng., v. BME-30, p. 377.

    Google Scholar 

  13. Witten, A. J., and King, W. C., 1990, Acoustic imaging of subsurface features: Jour. Env. Eng., v. 116, p. 166.

    Google Scholar 

  14. Sponheim, N., and Johansen, I., 1991, Experimental results in ultrasonic tomography using a altered back projection algorithm: Ultrasonic Imaging, v. 13, p. 56.

    Google Scholar 

  15. Sponheim, M., Johansen I., and Devaney, A. J., 1991, Initial testing of a clinical ultrasound monograph, in Bertero, M., and Pike, E. R., eds., Acoustic Imaging: Adam Hilger, Bristol, p. 401.

    Google Scholar 

  16. Ladas, K. T., and Devaney, A. J., 1993, Application of ART algorithmin an exp-erimental study of ultrasonic diffraction tomography: Ultrasonic Image, v. 15, p. 48.

    Google Scholar 

  17. Stamnes, J. J., Gelius, L-J., Johansen, I., and Sponheim, N., 1992, Diffraction tomography applications in seismics and medicine, in Bertero, M., and Pike, E. R., eds., Inverse Problems in Scattering and Imaging: Adam Hilger, Bristol, p. 268.

    Google Scholar 

  18. Dorn, O., Bertete-Aguirre, H., Berryman, J., and Papanicolaou, G., 1999, A nonlinear inversion method for 3D-electromagnetic imaging using adjoint fields: Inverse Problems, v. 15, p. 1523–1558.

    Google Scholar 

  19. Daily, W., and Ramirez, A., 1995, Environmental process tomography in the US: Chem. Eng. Jour. v. 56, p. 159–165.

    Google Scholar 

  20. Beck, M. S., Byars, M., Dyakowski, T., Waterfall, R., He, R., Wang, S. M., and Wang, W. Q., 1997, Principles and industrial applications of electrical capacitance tomography, Measurement and Control: v. 30, p. 197–200.

    Google Scholar 

  21. Isaacson, D., and Cheney, M., 1990, Current problems in impedance imaging, in Inverse Problems in Partial Differential Equation: SIAM, p. 151–149.

  22. Rudy, Y., and Messinger-Rapport, B. J., 1997, The inverse solution in electrocardiography: Solutions in terms of epicardial potentials: CRC Crit. Rev. Biomed. Eng., v. 16, p. 215–268.

    Google Scholar 

  23. Brooks, D. H., and MacLeod, R. S., 1997, Electrical imaging of the heart: Electrophysical underpinnings and signal processing opportunities: IEEE Sig. Proc. Mag., v. 14, p. 24–42.

    Google Scholar 

  24. MacLeod, R. S., and Brooks, D. H., 1998, Recent progress in inverse problems in electrocardiology: IEEE Eng. in Med. & Biol. Soc. Magazine, v. 17, p. 73–83.

    Google Scholar 

  25. Selker, H. P., 1989, Coronary care unit triage decision aids: How dowe know when they work?, Am. J. Med., v. 87, p. 491–493.

    Google Scholar 

  26. Siegel, A.M., Marota, J. J. A., and Boas, D. A., 1999, Design and evaluation of a continuous-wave diffuse optical tomography system: Optics Express, v. 4, p. 287–298.

    Google Scholar 

  27. Hintz S., Siegel, A. M., Benaron, D. A., and Boas, D. A., 1999, Bedside functional imaging of the premature infant brain during passive motor activation, in Chance, B., Alfano, R., Tromberg, B. J., eds., Optical tomography and spectroscopy of tissue III: Proc. SPIE 3597, p. 221–229.

  28. Dwyer, P. J., DiMarzio, C. A., and Anderson, R. R., 1997, Imaging of blood oxygenation in skin using four-wavelength reflectance spectroscopy: Biomedical Sensing, Imaging, and Tracking Technologies II, 2976, p. 270–280.

    Google Scholar 

  29. Dwyer, P. J., and DiMarzio, C. A., 1996, Algorithms for processing spectral reflectance images of tissue to obtain maps of oxygen saturation: Paper TuAA6, OSA Annual Meeting, Rochester, NY, October 21–24.

  30. Dwyer, P. J., et al., 1997, Imaging of blood oxygen saturation in skin using fourwavelength reflectance spectroscopy: submitted to IEEE Transactions on Biomedical Imaging.

  31. Wan, S., Anderson, R. R., and Parrish, A. J., 1991, Analytical modeling for the optical properties of the skin with in vitro and in vivo applications: Photochem. Photobiol., v. 34, p. 493–499.

    Google Scholar 

  32. Anderson, R. R., and Parrish, J. A., 1982, Optical properties of human skin: The Science of Photomedicine: Plenum Press, New York, p. 147–194.

    Google Scholar 

  33. Van Gemert, M. J. C., et al., 1989, Skin optics: IEEE Trans. on Biomed. Eng., v. 36, p. 12, ?1146.

    Google Scholar 

  34. Knuttel, A. J., Schmitt, J., and Knutson, J., 1993, Spatial localization of absorbing bodies by interfering discursive photon density waves: Applied Optics, v. 32, p. 381.

    Google Scholar 

  35. Svaasand, L., Tromberg, R., Haskell, T., and Berns, M., 1993, Tissue characterization and imaging using photon density wave: Optical Engineering, 32, 258.

    Google Scholar 

  36. Huang, D., et al., 1991, Optical coherence tomography: Science, v. 254, p. 1178–1181.

    Google Scholar 

  37. Brazinski, M. E., et al., 1996, Optical coherence tomography for optical biopsy: Circulation, v. 93, p. 1206–1213.

    Google Scholar 

  38. Beneron, D., et al., 1997, Tissue optics: Science, v. 276, p. 2002–2003.

    Google Scholar 

  39. DiMarzio, C. A., and Gaudette, T. J., 1999, A new imaging technique combining diffusive photon density waves and focussed ultrasound: Optical Tomography and Spectroscopy of Tissue III, Proc. SPIE 3597, Paper 3597±59 BIOS 99, San Jose, CA, January.

  40. Jimenez, L. O., and Velez-Reyes, W., 1998, Subset selection analysis for the reduction of hyperspectral imagery: Proc. IEEE International Geosciences and Remote Sensing Symposium, Seattle, WA.

  41. Akira Ishimaru, 1997, Wave propagation and scattering in random media: IEEE Press, New York.

    Google Scholar 

  42. Appenzeller, T., and Norman, C., 1997, Imaging: new eyes on hidden worlds: Science, v. 276, p. 1981–1995.

    Google Scholar 

  43. Russel, M., Colglazier, E. W., and English, M. R., 1991, Hazardous waste remediation—The task ahead: Knoxville, Waste Management Research and Education Institute, University of Tennessee.

  44. National Science Foundation Engineering Research Centers Program Announcement NSF 98–146, Supplemental Full Proposal Guidelines and Format.

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Authors and Affiliations

  1. Center for Subsurface Sensing and Imaging Systems (CenSSIS), Northeastern University, Boston, MA, 02115, USA

    C. Rappaport

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  1. M. B. Silevitch
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  2. S. W. McKnight
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  3. C. Rappaport
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Silevitch, M.B., McKnight, S.W. & Rappaport, C. A Unified Discipline of Subsurface Sensing and Imaging Systems. Subsurface Sensing Technologies and Applications 1, 3–21 (2000). https://doi.org/10.1023/A:1010118225009

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