Preclinical Prototype Development of a Microwave Tomography System for Breast Cancer Detection

ETRI Journal

关键词: nonlinear inverse problem;    electromagnetic inverse scattering;    microwave imaging;    microwave tomography;    Cancer detection;   

Others  :  1185873
DOI  :  10.4218/etrij.10.0109.0626

【 摘 要 】

As a supplement to X-ray mammography, microwave imaging is a new and promising technique for breast cancer detection. Through solving the nonlinear inverse scattering problem, microwave tomography (MT) creates images from measured signals using antennas. In this paper, we describe a developed MT system and an iterative Gauss-Newton algorithm. At each iteration, this algorithm determines the updated values by solving the set of normal equations using Tikhonov regularization. Some examples of successful image reconstruction are presented.

   

【 参考文献 】

• [1]M. Garcia et al., Global Cancer Facts and Figures, Atlanta, GA: American Cancer Society, 2007.
• [2]P.M. Meaney et al., "Microwave Image Reconstruction Utilizing Log-Magnitude and Unwrapped Phase to Improve High-Contrast Object Recovery," IEEE Trans. Medical Imaging, vol. 20, no. 2, Feb. 2001, pp. 104-116.
• [3]Q. Fang, Computational Methods for Microwave Medical Imaging, Ph.D. Thesis, Dartmouth College, Hanover, Dec. 2004.
• [4]I. Hieda and K.C. Nam, "2D Image Construction from Low Resolution Response of a New Non-invasive Measurement for Medical Application," ETRI J., vol. 27, no. 4, 2005, pp. 385-393.
• [5]S.Y. Semenov et al., "Microwave Tomographic Imaging of the High Dielectric-Contrast Objects Using Different Image-Reconstruction Approaches," IEEE Trans. Microw. Theory Tech., vol. 53, no. 7, 2005, pp. 2284-2294.
• [6]T. Rubæk et al., "Nonlinear Microwave Imaging for Breast-Cancer Screening Using Gauss–Newton’s Method and the CGLS Inversion Algorithm," IEEE Trans. Antennas Propag., vol. 55, no. 8, Aug. 2007, pp. 2320-2331.
• [7]E.J. Bond et al., "Microwave Imaging via Space-Time Beamforming for Early Detection of Breast Cancer," IEEE Trans. Antennas Propag., vol. 51, no. 8, Aug. 2003, pp. 1690-1705.
• [8]J.M. Sill and E.C. Fear, "Tissue Sensing Adaptive Radar for Breast Cancer Detection–Experimental Investigation of Simple Tumor Models," IEEE Trans. Microw. Theory Tech., vol. 53, no. 11, Nov. 2005, pp. 3312-3319.
• [9]Yao Xie et al., "Multistatic Adaptive Microwave Imaging for Early Breast Cancer Detection." IEEE Trans. Biomed. Eng., vol. 53, no. 8, Aug. 2006, pp. 1647-1657.
• [10]S. Semenov, "Microwave Tomography: Review of the Progress towards Clinical Applications," Phil. Trans. R. Soc. A, vol. 367, no. 1900, 2009, pp. 3021-3042.
• [11]Cellular Telephone Specific Absorption Rate. Available: http:// www.fcc.gov/cgb/sar/
• [12]P.J. Cameron, "Discrete Mathematics and its Applications," Handbook of Linear Algebra, L. Hogben, Ed. NY: Chapman & Hall/CRC, Taylor & Francis Group, 2007.
• [13]Y. Oshikane et al., "Observation of Nanostructure by Scanning Near-Field Optical Microscope with Small Shere Probe," Sci. Technol. Adv. Mater., vol. 8, no. 3, Apr. 2007, pp. 181-185.
• [14]C.E. Shannon, "Communication in the Presence of Noise," Proc. Institute of Radio Engineers, vol. 37, no.1, Jan. 1949, pp. 10-21. Reprinted as classic paper in Proc. IEEE, vol. 86, no. 2, Feb. 1998.
• [15]P.C. Hansen, Rank-Deficient and Discrete Ill-Posed Problems: Numerical Aspects of Linear Inversion, SIAM, Philadelphia, 1997.