Morphological Reconstruction Improves Microvessel Mapping in Super-Resolution Ultrasound

Scott Schoen, Zhigen Zhao, Ashley Alva, Chengwu Huang, Shigao Chen, Costas Arvanitis

Research output: Contribution to journalArticlepeer-review

Abstract

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 trade-offs, we propose a method based on morphological image reconstruction. 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.

Keywords

  • acoustic cavitation
  • Image reconstruction
  • Location awareness
  • Optical filters
  • Optical imaging
  • Spatial resolution
  • super-resolution
  • Superresolution
  • Ultrasonic imaging
  • ultrasound imaging

ASJC Scopus subject areas

  • Instrumentation
  • Acoustics and Ultrasonics
  • Electrical and Electronic Engineering

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