Automatic Detection of Extra-Cardiac Findings in Cardiovascular Magnetic Resonance

Dewmini Hasara Wickremasinghe*, Natallia Khenkina, Pier Giorgio Masci, Andrew P. King, Esther Puyol-Antón

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


Cardiovascular magnetic resonance (CMR) is an established, non-invasive technique to comprehensively assess cardiovascular structure and function in a variety of acquired and inherited cardiac conditions. In addition to the heart, a typical CMR examination will also image adjacent thoracic and abdominal structures. Consequently, findings incidental to the cardiac examination may be encountered, some of which may be clinically relevant. We compare two deep learning architectures to automatically detect extra cardiac findings (ECFs) in the HASTE sequence of a CMR acquisition. The first one consists of a binary classification network that detects the presence of ECFs and the second one is a multi-label classification network that detects and classifies the type of ECF. We validated the two models on a cohort of 236 subjects, corresponding to 5610 slices, where 746 ECFs were found. Results show that the proposed methods have promising balanced accuracy and sensitivity and high specificity.

Original languageEnglish
Title of host publicationMedical Image Understanding and Analysis - 25th Annual Conference, MIUA 2021, Proceedings
EditorsBartłomiej W. Papież, Mohammad Yaqub, Jianbo Jiao, Ana I. Namburete, J. Alison Noble
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages10
ISBN (Print)9783030804312
Publication statusPublished - 2021
Event25th Annual Conference on Medical Image Understanding and Analysis, MIUA 2021 - Virtual, Online
Duration: 12 Jul 202114 Jul 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12722 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference25th Annual Conference on Medical Image Understanding and Analysis, MIUA 2021
CityVirtual, Online


  • Cardiovascular magnetic resonance
  • Deep learning classification
  • Extra cardiac findings


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