A Compressive Sensing Unmixing Algorithm for Breast Cancer Detection

Traditional breast cancer imaging methods using microwave imaging (MWI) seek to recover the complex permittivity of the tissues at each voxel in the imaging region. This approach is suboptimal in that it does not directly consider the permittivity values that healthy and cancerous breast tissues typically have. The authors describe a novel unmixing algorithm for detecting breast cancer. In this approach, the breast tissue is separated into three components, low water content, high water content, and cancerous tissues, and the goal of the optimisation procedure is to recover the mixture proportions of each component. By utilising this approach in a hybrid digital breast tomosynthesis/MWI system, the unmixing reconstruction process can be posed as a sparse recovery problem such that compressive sensing techniques can be employed. A numerical analysis is performed, which demonstrates that cancerous lesions can be detected from their mixture proportion under the appropriate conditions.