Morphological Reconstruction Improves Microvessel Mapping in Super-Resolution Ultrasound

TL;DR

This paper introduces a morphological reconstruction method that significantly enhances microvessel mapping in super-resolution ultrasound images, achieving higher detection rates, improved spatial resolution, and robustness to noise, thereby advancing clinical imaging capabilities.

Contribution

The proposed morphological reconstruction technique improves microbubble peak detection and spatial resolution in super-resolution ultrasound imaging, offering a fast, noise-robust, and scalable solution.

Findings

Fourfold increase in microbubble peak detection per frame.

Sixfold improvement in spatial resolution of microvessel imaging.

Robust performance with low electronic noise levels.

Abstract

Generation of super-resolution (SR) ultrasound (US) images, created from the successive local-ization of individual microbubbles in the circulation, has enabled the visualization of microvascular structure and flow at a level of detail that was not possible previously. Despite rapid progress, tradeoffs between spatial and temporal resolution may challenge the translation of this promising technology to the clinic. To temper these trade-offs, we propose a method based on morphological image reconstriction. This method can extract from ultrafast contrast-enhanced ultrasound (CEUS) images hundreds of microbubble peaks per image (312-by-180 pixels) with intensity values varying by an order of magnitude. Specifically, it offers a fourfold increase in the number of peaks detected per frame, requires on the order of 100 ms for processing, and is robust to additive electronic noise (down to 3.6 dB CNR in CEUS images). By integrating this method to a SR framework we demonstrate a 6-fold improvement in spatial resolution, as compared to CEUS, in imaging chicken embryo microvessels. This method that is computationally efficient and, thus, scalable to large data sets, may augment the abilities of SR-US in imaging microvascular structure and function.