Enhancement of Gauss–Newton Inversion Method for Biological Tissue Imaging

Abstract

The multiplicatively regularized Gauss-Newton inversion (GNI) algorithm is enhanced and utilized to obtain complex permittivity profiles of biological objects-of-interest. The microwave scattering data is acquired using a microwave tomography system comprised of 24 co-resident antennas immersed into a saltwater matching fluid. Two types of biological targets are imaged: ex vivo bovine legs and in vivo human forearms. Four different forms of the GNI algorithm are implemented: a blind inversion, a balanced inversion, a shape-and-location inversion, and a novel balanced shape-and-location inversion. The latter three techniques incorporate typical permittivity values of biological tissues as prior information to enhance the reconstructions. In those images obtained using the balanced shape-and-location reconstruction algorithm, the various parts of the tissue being imaged are clearly distinguishable. The reconstructed permittivity values in the bovine leg images agree with those obtained via direct measurement using a dielectric probe. The reconstructed images of the human forearms qualitatively agree with magnetic resonance imaging images, as well as with the expected dielectric values obtained from the literature.