Advanced image reconstruction for high-resolution 3D breast ultrasound tomography
Abstract: Ultrasound computed tomography (USCT) is an emerging medical imaging modality that can produce quantitative images of acoustic properties of tissue. In this talk, recent advances in image reconstruction are reviewed. These include: 1) the develop of realistic stochastic numerical breast phantoms to enable meaningful evaluations of breast USCT via virtual imaging studies; 2) a 3D numerical forward model for USCT with consideration of elevation-focused transducers, for use with ring array-based imagers; and 3) a deep learning (DL)-based reconstruction procedure for USCT that seeks to achieve image quality similar to that produced by full waveform inversion methods but at a reduced computational cost.
Bio: Fu Li is a Ph.D. student at the Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, Illinois. He received his B.S. degree in information and computing science from Sun Yat-sen University, Guangzhou, China. His research interests include ultrasound computed tomography and machine learning in medical imaging applications
