Inversion Algorithm for Microwave Breast Cancer Detection Using Level Sets

This work focuses on the application of breast cancer detection from microwave data. We present a novel shape-based reconstruction algorithm that makes use of level set techniques. Our reconstruction algorithm consists of several stages of increasing complexity in which more details of the anatomical structure of the breast interior are incorporated successively. In particular, the algorithm approximates first the fibroglandular and fatty regions, and then determines the presence and characteristics of the tumor, such as its size and dielectric properties. The shape-based approach implies an implicit regularization of the inverse problem that creates the images, in the form of prior knowledge regarding the types of tissues present in the breast. This reduces the dimensionality of the inverse problem helping to stabilize the reconstruction process. In addition, it provides well de¯ned interfaces between the tissues. Our results demostrate the potential and feasibility of this approach to detect, locate, and characterize tumors in their early stages of development.

Inversion Algorithm for Microwave Breast Cancer Detection Using Level Sets Articles