Deep-learning-based washout classification for decision support in contrast-enhanced ultrasound examinations of the liver.

Hannah Strohm¹, Sven Rothlübbers¹, Jürgen Jenne¹, Dirk-André Clevert², Thomas Fischer³, Niklas Hitschrich⁴, Bernhard Mumm⁴, Paul Spiesecke³, Matthias Günther^1,5

¹Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany.

²Ludwig-Maximilians-University Munich, Department of Radiology, Munich, Germany.

³Charité-Universitätsmedizin Berlin, Interdisciplinary Ultrasound Center, Department of Radiology, Berlin, Germany.

⁴TOMTEC Imaging Systems, Unterschleißheim, Germany.

⁵University of Bremen, Bremen, Germany.

PubMed PMC DOI PDF

Abstract

PURPOSE: Contrast-enhanced ultrasound (CEUS) is a reliable tool to diagnose focal liver lesions, which appear ambiguous in normal B-mode ultrasound. However, interpretation of the dynamic contrast sequences can be challenging, hindering the widespread application of CEUS. We investigate the use of a deep-learning-based image classifier for determining the diagnosis-relevant feature washout from CE…

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