A Nonlinear Microwave Breast Cancer Imaging Approach Through Realistic Body-Breast Modeling

Gurbuz T. U., ASLANYÜREK B., Yapar A., ŞAHİNTÜRK H., Akduman İ.

IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, cilt.62, sa.5, ss.2596-2605, 2014 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 62 Sayı: 5
  • Basım Tarihi: 2014
  • Doi Numarası: 10.1109/tap.2014.2307303
  • Dergi Adı: IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.2596-2605
  • Anahtar Kelimeler: Breast cancer imaging, buried object approach, Green's function, microwave tomography, nonlinear inverse scattering, DIELECTRIC-PROPERTIES, NUMERICAL BREAST, GREENS-FUNCTION, LARGE-SCALE, SCATTERING, PHANTOMS, TISSUES, SYSTEM, WAVES
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

A nonlinear microwave tomography approach which suggests monitoring of differences inside the breast with respect to a reference breast model that adequately represents the healthy breast is presented. This approach simplifies the breast cancer imaging problem through realistic modeling of the body-breast configuration and does not require the imaging of the entire breast tissues. The tumor is considered as a buried object inside the breast which is assumed to be located on the interface of two-half spaces media composed of air or a coupling liquid and the chest wall or the base of the bed on which patient lies in a prone position. Then, the tumor, as well as the deviations of the actual breast from the breast model, is imaged by using the contrast source inversion method at a single frequency. The Green's function of the inhomogeneous background required in the application of the inversion algorithm is obtained through the buried object approach and accelerated by an adaptation of the discrete complex images method. Through the simulations it has been shown that, the proposed modeling and nonlinear inversion algorithm is capable of reconstructing tumors as small as 4 mm in radius for 3-D scenarios.