Ultrasound spectroscopy

Abstract

We introduce the concept of “Ultrasound Spectroscopy”. The premise of ultrasound spectroscopy is that by acquiring ultrasound RF data at multiple power and frequency settings, a rich set of features can be extracted from that RF data and used to characterize the underlying tissues. This is beneficial for a variety of problems, such as accurate tissue classification, application-specific image generation, and numerous other quantitative tasks. These capabilities are particularly relevant to point-of-care ultrasound (POCUS) applications, where operator experience with ultrasound may be limited. Instead of displaying B-mode images, a POCUS application using ultrasound spectroscopy can, for example, automatically detect internal abdominal bleeding. In this paper, we present ex vivo tissue phantom studies to demonstrate the accuracy of ultrasound spectroscopy over previous approaches. Our studies suggest that ultrasound spectroscopy provides exceptional accuracy and informative features for classifying blood versus other tissues across image locations and body habitus.

Publication
13th IEEE International Symposium on Biomedical Imaging, ISBI 2016, Prague, Czech Republic, April 13-16, 2016
Marc Niethammer
Marc Niethammer
Professor of Computer Science

My research interests include image registration, image segmentation, shape analysis, machine learning, and biomedical applications.

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