Fast High Resolution Blood Flow Estimation and Clutter Rejection via an Alternating Optimization Problem

TL;DR

This paper presents a fast, efficient method for high-resolution blood flow estimation in ultrasound imaging, utilizing an alternating minimization algorithm and robust PCA for improved clutter rejection.

Contribution

It introduces a novel fast alternating optimization algorithm for blind deconvolution in Doppler blood flow estimation, enhancing computational efficiency and accuracy.

Findings

Outperforms state-of-the-art methods in numerical tests

Effective clutter rejection in high-resolution blood flow imaging

Demonstrated on in vivo ultrasound data

Abstract

This paper introduces a computationally efficient technique for estimating high-resolution Doppler blood flow from an ultrafast ultrasound image sequence. More precisely, it consists in a new fast alternating minimization algorithm that implements a blind deconvolution method based on robust principal component analysis. Numerical investigation carried out on \textit{in vivo} data shows the efficiency of the proposed approach in comparison with state-of-the-art methods.