Adaptive Time-Channel Beamforming for Time-of-Flight Correction

TL;DR

This paper introduces the adaptive time-channel (ATC) beamformer, a data-driven method that enhances ultrasound imaging resolution, contrast, and noise reduction by integrating spatial and temporal information for improved time-of-flight correction.

Contribution

The paper presents a novel ATC beamformer that generalizes minimum variance beamformers by combining spatial and temporal data, and extends apodization to the temporal domain.

Findings

12% resolution enhancement

2-fold contrast improvement

Significant noise reduction

Abstract

Adaptive beamforming can lead to substantial improvement in resolution and contrast of ultrasound images over standard delay and sum beamforming. Here we introduce the adaptive time-channel (ATC) beamformer, a data-driven approach that combines spatial and temporal information simultaneously, thus generalizing minimum variance beamformers. Moreover, we broaden the concept of apodization to the temporal dimension. Our approach reduces noises by allowing for the weights to adapt in both the temporal and spatial dimensions, thereby reducing artifacts caused by the media's inhomogeneities. We apply our method to in-silico data and show 12% resolution enhancement along with 2-fold contrast improvement, and significant noise reduction with respect to delay and sum and minimum variance beamformers.