Ultrasound localization microscopy lite (ULM lite): ultrasound localization microscopy with resource-efficient signal processing scheme

Abstract

Ultrasound localization microscopy (ULM) is a groundbreaking, non-invasive imaging tool for monitoring vascular hemodynamics and neuronal activities in rodent models with exceptional spatial resolution. Despite its potential, the extensive data size required by the current ULM framework poses significant limitations to its broader applications. This study addresses these challenges by introducing sub-Nyquist sampling of the bandlimited radio-frequency (RF) signals, a method designed to reduce resource demands while preserving image quality. In this study, we experimentally demonstrate the in vivo feasibility of the proposed method. Our results show that 67 % of band-limited signal images achieve a high signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), comparable to those of conventional 200 % bandwidth signals. Even under stringent data reduction conditions, the proposed approach reduces the data size by approximately one-third without compromising image quality. These results highlight the potential of the proposed approach holds significant promise for enhancing the efficiency and practicality of ULM, facilitating the non-invasive visualization of deep neuronal activities with improved resource efficiency.