LAUSR

ABSTRACT Early detection of breast cancer will continue to be crucial in improving patient survival rates for the foreseeable future. Our long-term goal is to automate and refine the manual breast exam process using measured data on the breast surface in combination with formal inverse techniques to generate three-dimensional maps of the stiffness inside the breast tissue. In this paper, we report on computational techniques that use force measurements to create the stiffness map and validate the computational techniques experimentally with silicone tissue phantom experiments. We conducted 16 tests on tumour-free phantom samples and 16 tests on tumour-containing phantoms. Our stiffness mapping approach resulted in one false positive and a correct identification of the remaining 31/32 samples.