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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
computer science
A collaborative resource to build consensus for automated left ventricular segmentation of cardiac MR images
Medical Image Analysis, Volume 18, No. 1, Year 2014
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Description
A collaborative framework was initiated to establish a community resource of ground truth segmentations from cardiac MRI. Multi-site, multi-vendor cardiac MRI datasets comprising 95 patients (73 men, 22 women; mean age 62.73. ±. 11.24. years) with coronary artery disease and prior myocardial infarction, were randomly selected from data made available by the Cardiac Atlas Project ( Fonseca et al., 2011). Three semi- and two fully-automated raters segmented the left ventricular myocardium from short-axis cardiac MR images as part of a challenge introduced at the STACOM 2011 MICCAI workshop ( Suinesiaputra et al., 2012). Consensus myocardium images were generated based on the Expectation-Maximization principle implemented by the STAPLE algorithm ( Warfield et al., 2004). The mean sensitivity, specificity, positive predictive and negative predictive values ranged between 0.63 and 0.85, 0.60 and 0.98, 0.56 and 0.94, and 0.83 and 0.92, respectively, against the STAPLE consensus. Spatial and temporal agreement varied in different amounts for each rater. STAPLE produced high quality consensus images if the region of interest was limited to the area of discrepancy between raters. To maintain the quality of the consensus, an objective measure based on the candidate automated rater performance distribution is proposed. The consensus segmentation based on a combination of manual and automated raters were more consistent than any particular rater, even those with manual input. The consensus is expected to improve with the addition of new automated contributions. This resource is open for future contributions, and is available as a test bed for the evaluation of new segmentation algorithms, through the Cardiac Atlas Project ( www.cardiacatlas.org). © 2013 Elsevier B.V.
Authors & Co-Authors
Suinesiaputra, Avan
New Zealand, Auckland
The University of Auckland
Cowan, Brett R.
New Zealand, Auckland
The University of Auckland
Al-Agamy, Ahmed O.
Egypt, 6th October
Nile University
Elattar, Mustafa
United States, Morrisville
Diagnosoft Inc.
Ayache, Nicholas
France, Sophia Antipolis
Centre Inria Sophia Antipolis - Méditerranée
Fahmy, Ahmed S.
Egypt, 6th October
Nile University
Egypt, Cairo
Faculty of Engineering
Khalifa, Ayman M.
United States, Morrisville
Diagnosoft Inc.
Egypt, Helwan
Faculty of Engineering Helwan
Medrano-Gracia, Pau
New Zealand, Auckland
The University of Auckland
Jolly, Marie Pierre Dubuisson
United States, New York
Siemens Usa
Kadish, Alan H.
United States, Chicago
Northwestern University Feinberg School of Medicine
Lee, Daniel C.
United States, Chicago
Northwestern University Feinberg School of Medicine
Margeta, Ján
France, Sophia Antipolis
Centre Inria Sophia Antipolis - Méditerranée
Warfield, Simon K.
United States, Boston
Harvard Medical School
Young, Alistair A.
New Zealand, Auckland
The University of Auckland
Statistics
Citations: 165
Authors: 14
Affiliations: 9
Identifiers
Doi:
10.1016/j.media.2013.09.001
ISSN:
13618415
e-ISSN:
13618423
Research Areas
Noncommunicable Diseases
Participants Gender
Male
Female