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Development of Effective Analytical Signal Models for Functional Microwave Imaging

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Various active microwave imaging techniques have been developed for cancer detection for past several decades. Both the microwave tomography and the UWB radar techniques, constituting functional microwave imaging systems, use the electrical property contrast between normal tissues and malignancies to detect the latter in an early development stage. Even though promising simulation results have been reported, the understanding of the functional microwave imaging diagnostics has been relied heavily on the complicated numerical results. We present a computationally efficient and physically instructive analytical electromagnetic wave channel models developed for functional microwave imaging system in order to detect especially the breast tumors as early as possible. The channel model covers the propagation factors that have been examined in the previous 2-D models, such as the radial spreading, path loss, partial reflection and transmission of the backscattered electromagnetic waves from the tumor cell. The effects of the system noise and the noise from the inhomogeneity of the tissue to the reconstruction algorithm are modeled as well. The characteristics of the reconstructed images of the tumor using the proposed model are compared with those from the confocal microwave imaging.

Abstract

Various active microwave imaging techniques have been developed for cancer detection for past several decades. Both the microwave tomography and the UWB radar techniques, constituting functional microwave imaging systems, use the electrical property contrast between normal tissues and malignancies to detect the latter in an early development stage. Even though promising simulation results have been reported, the understanding of the functional microwave imaging diagnostics has been relied heavily on the complicated numerical results. We present a computationally efficient and physically instructive analytical electromagnetic wave channel models developed for functional microwave imaging system in order to detect especially the breast tumors as early as possible. The channel model covers the propagation factors that have been examined in the previous 2-D models, such as the radial spreading, path loss, partial reflection and transmission of the backscattered electromagnetic waves from the tumor cell. The effects of the system noise and the noise from the inhomogeneity of the tissue to the reconstruction algorithm are modeled as well. The characteristics of the reconstructed images of the tumor using the proposed model are compared with those from the confocal microwave imaging.

참고문헌 (7)

  1. E. C. Fear, "Confocal microwave imaging for breast cancer detection: localization of tumors in three dimensions", 49, pp.812~821 (2002)
  2. A. Taflove, "Three-dimensional FDTD analysis of a pulsed microwave confocal system for breast cancer detection: design of an antenna-array element", 47, pp.783~791 (1999)
  3. E. C. Fear, "Enhancing breast tumor detection with near-field imaging", pp.48~56 (2002)
  4. S. C. Hagness, "FDTD analysis of a pulsed microwave confocal system for breast cancer detection", pp.2506~2508 (1997)
  5. S. C. Hagness, "Two-dimensional FDTD analysis of a pulsed microwave confocal system for breast cancer detection: fixed focus and antenna-array sensors", 45, pp.1470~1479 (1998), fixed focus and antenna-array sensors
  6. X. Li, "A confocal microwave imaging algorithm for breast cancer detection", 11, pp.130~132 (2001)
  7. W. Hayt, "Engineering Electromagnetics", pp.356~365 (2001), McGraw-Hill

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