tiDAS: a time invariant approximation of the Delay and Sum algorithm for biomedical ultrasound PSF reconstructions

TL;DR

This paper introduces tiDAS, a computationally efficient approximation of the DAS algorithm for ultrasound imaging that maintains image quality while enabling faster real-time reconstructions.

Contribution

The authors propose a novel time-invariant approximation of DAS using a row-wise convolutional approach, reducing computational complexity in ultrasound beamforming.

Findings

tiDAS significantly speeds up image reconstruction

tiDAS maintains comparable image quality to traditional DAS

Synthetic experiments confirm the efficiency and accuracy of tiDAS

Abstract

Ultrasound imaging is a real-time diagnostic modality that reconstructs acoustic signals into visual representations of internal body structures. A key component in this process is beamforming, with the Delay and Sum (DAS) algorithm being a standard due to its balance between simplicity and effectiveness. However, the computational cost of DAS can be a limiting factor, especially in real-time scenarios where fast frame reconstruction is essential. In this work, we introduce a time-invariant approximation of the DAS algorithm (tiDAS), designed to accelerate the reconstruction process without compromising image quality. By adopting a one-dimensional, row-wise convolutional formulation, tiDAS significantly reduces computational complexity while preserving the core properties of the original model. This approach not only enables faster image reconstruction but also provides a structured foundation for the application of deconvolution methods aimed at enhancing resolution. Synthetic experiments demonstrate that tiDAS achieves a favorable trade-off between speed and accuracy, making it a promising tool for improving the efficiency of real-time ultrasound imaging.