Millimeter-wave breast cancer imaging by means of a dual-step approach combining radar and tomographic techniques: preliminary results.

Breast cancer is one of the most diagnosed forms of cancer among women worldwide. However, the survival rate is very high when the tumor is diagnosed early. The search for diagnostic techniques increasingly able to detect lesions of the order of a few millimeters and to overcome the limitations of current diagnostic techniques (e.g., the X-ray mammography, currently used as standard for screening campaigns) is always active. Among the main emerging techniques, microwave and millimeter-wave imaging systems have been proposed, using either radar or tomographic approaches. In this paper, a novel dual-step millimeter-wave imaging which combines the advantages of tomographic and radar approaches is proposed. The goal of this work is to reconstruct the dielectric profile of suspicious regions by exploiting the morphological information from the radar maps as a priori information within quantitative tomographic techniques. Promising preliminary dielectric reconstruction results against simulated data are shown in both single- and dual-target scenarios, in which high-density healthy and tumor tissues are present. The reconstruction results were compared to the dielectric characteristics of human breast exvivo tissues used in the simulated models. The proposed dual-step approach allows to distinguish the nature of the targets also in the most challenging case represented by the co-presence of high-density healthy tissues and a malignant lesion, thus paving the way for a deeper investigation of this approach in experimental scenarios. Clinical Relevance-The proposed dual-step approach in the millimeter-wave regime allows to improve the reliability of the diagnostic technique, increasing its specificity.

Improved TV-CS Approaches for Inverse Scattering Problem.

Total Variation and Compressive Sensing (TV-CS) techniques represent a very attractive approach to inverse scattering problems. In fact, if the unknown is piecewise constant and so has a sparse gradient, TV-CS approaches allow us to achieve optimal reconstructions, reducing considerably the number of measurements and enforcing the sparsity on the gradient of the sought unknowns. In this paper, we introduce two different techniques based on TV-CS that exploit in a different manner the concept of gradient in order to improve the solution of the inverse scattering problems obtained by TV-CS approach. Numerical examples are addressed to show the effectiveness of the method.