Block-wise Independent Component Analysis for Slow Flow Non-Contrast Ultrasound Imaging

Abstract

Slow blood flow imaging has proven to be a difficult clinical problem. Imaging modalities, such as MR Angiography and Contrast-Enhanced Ultrasound, attempting to solve this problem are expensive and time-consuming. Both eigen-based filters and spatial filters have been proposed to improve ultrasound power Doppler blood flow images. Block-wise methods and Independent Component Analysis (ICA) filters have each individually been previously shown to improve tissue clutter and noise suppression. Here, we aim to develop a Block-wise implementation of ICA to evaluate blood flow in ultrasound blood flow imaging. We show through phantom studies that by applying ICA in a block-wise manner, we see qualitative improvements as compared to other eigen-based filters applied in global and block-wise manners.