4.6 Article

Morphological Reconstruction Improves Microvessel Mapping in Super-Resolution Ultrasound

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TUFFC.2021.3057540

Keywords

Ultrasonic imaging; Optical filters; Spatial resolution; Optical imaging; Image reconstruction; Superresolution; Location awareness; Acoustic cavitation; super-resolution (SR); ultrasound (US) imaging

Funding

  1. NIH [R00EB016971, R37CA239039]

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The generation of super-resolution ultrasound images through the localization of individual microbubbles has allowed for improved visualization of microvascular structure and flow. A method based on morphological image reconstruction has been proposed to increase peak detection and spatial resolution, with robustness to noise. This computationally efficient method shows promise for enhancing the capabilities of super-resolution ultrasound imaging.
Generation of super-resolution (SR) ultrasound (US) images, created from the successive localization 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 tradeoffs, we propose a method based on morphological image reconstruction. This method can extract from ultrafast contrast-enhanced US (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 an SR framework, we demonstrate a sixfold improvement in spatial resolution, when compared with 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.

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