Semi-automated Processing of Real-Time CMR Scans for Left Ventricle Segmentation

Rahil Shahzad*, Martin Fasshauer, Boudewijn P.F. Lelieveldt, Joachim Lotz, Rob J. van der Geest

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review


We present a workflow for processing real-time cardiac MR (RT-CMR) scans for segmenting the left ventricle (LV) on short-axis slices (SAX). Our method is based on image registration, where the LV endocardium and epicardium are segmented by propagating a reference contour over all the frames of the RT-CMR SAX scans. Our method was evaluated on 19 subjects, the accuracy of the automatic LV endocardium and epicardium segmentation was compared to those defined manually. The proposed method obtained a dice similarity coefficient (DSC) of 0.94 and a mean surface-to-surface distance (MSD) measure of 0.89 ± 0.53 mm. Additionally, a number of automatically obtained clinical measures were compared to ground truth values. On average we obtained a Pearson’s correlation coefficient (R) of 0.94 (0.99–0.74).

Original languageEnglish
Title of host publicationBiomedical Image Registration - 8th International Workshop, WBIR 2018 - Proceedings
EditorsStefan Klein, Marius Staring, Stanley Durrleman, Stefan Sommer
Place of PublicationCham
Number of pages10
ISBN (Electronic)978-3-319-92258-4
ISBN (Print)978-3-319-92257-7
Publication statusPublished - 2018
EventWBIR 2018: 8th International Workshop on Biomedical Image Registration - Leiden, Netherlands
Duration: 28 Jun 201829 Jun 2018
Conference number: 8

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10883 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


WorkshopWBIR 2018
Internet address


  • Left ventricle
  • Realtime-MR
  • Registration
  • Segmentation
  • Semi-automatic


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