Artificial Intelligence in Quantitative Ultrasound Imaging: A Review [article]

Boran Zhou, Xiaofeng Yang, Tian Liu
<span title="2020-03-25">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Quantitative ultrasound (QUS) imaging is a reliable, fast and inexpensive technique to extract physically descriptive parameters for assessing pathologies. Despite its safety and efficacy, QUS suffers from several major drawbacks: poor imaging quality, inter- and intra-observer variability which hampers the reproducibility of measurements. Therefore, it is in great need to develop automatic method to improve the imaging quality and aid in measurements in QUS. In recent years, there has been an
more &raquo; ... ncreasing interest in artificial intelligence (AI) applications in ultrasound imaging. However, no research has been found that surveyed the AI use in QUS. The purpose of this paper is to review recent research into the AI applications in QUS. This review first introduces the AI workflow, and then discusses the various AI applications in QUS. Finally, challenges and future potential AI applications in QUS are discussed.
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="">arXiv:2003.11658v1</a> <a target="_blank" rel="external noopener" href="">fatcat:iujuh7gra5ax7od2gxoo6yrbpe</a> </span>
<a target="_blank" rel="noopener" href="" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] </button> </a> <a target="_blank" rel="external noopener" href="" title=" access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> </button> </a>