Breast Cancer Imaging by Source-Extended Full-Waveform Inversion

Medical imaging constantly seeks more advanced methods to improve resolution and accessibility. Ultrasonic imaging is a safe, inexpensive, and widely used diagnostic tool. Full-waveform inversion (FWI) is a popular method within ultrasonic imaging, and source-extended or iteratively refined wavefield reconstruction inversion (IR- WRI) is an improved version that reduces the sensitivity of the problem to the initial model. In this study, we propose an application of IR- WRI for breast cancer imaging. The IR- WRI algorithm reconstructs the speed of sound (SOS) and attenuation by breaking the problem into sub-problems associated with each variable and wavefield. These sub-problems are solved in an alternating manner using the alternating direction method of multipliers (ADMM). Total-variation (TV) regularization is applied to mitigate the ill-posedness of the problem and reconstruct more meaningful biological tissues. To test our proposed method, we used a type C phantom breast containing three malignant lesions. Our method significantly improved anatomical resolution starting from a rough initial guess for the SOS and attenuation model. The results demonstrated proper reconstruction of the models and successful detection of anomalies. Our proposed algorithm represents a useful step toward improving settings for breast cancer imaging. By leveraging the advantages of IR-WRI and TV regularization, our method shows promise for achieving better resolution and accuracy in the detection of breast cancer.