Infarct segmentation challenge on delayed enhancement MRI of the left ventricle

Karim, Rashed, Claus, Piet, Chen, Zhong, Housden, R. James, Obom, Samantha, Gill, Harminder, Ma, YingLiang ORCID: https://orcid.org/0000-0001-5770-5843, Acheampong, Prince, O'Neill, Mark, Razavi, Reza, Schaeffter, Tobias and Rhode, Kawal S. (2013) Infarct segmentation challenge on delayed enhancement MRI of the left ventricle. In: Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges. Lecture Notes in Computer Science . Springer, 97–104. ISBN 978-3-642-36960-5

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Abstract

This paper presents collated results from the Delayed Enhancement MRI (DE-MRI) segmentation challenge at MICCAI 2012. DE-MRI Images from fifteen patients and fifteen pigs were randomly selected from two different imaging centres. Three independent sets of manual segmentations were obtained for each image and included in this study. A ground truth consensus segmentation based on all human rater segmentations was obtained using an Expectation-Maximization (EM) method (the STAPLE method). Automated segmentations from five groups contributed to this challenge.

Item Type:	Book Section
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Norwich Epidemiology Centre Faculty of Medicine and Health Sciences > Research Groups > Norwich Epidemiology Centre Faculty of Science > Research Groups > Data Science and AI
Related URLs:	http://www.scopus.com/inward/record.url?...
Depositing User:	LivePure Connector
Date Deposited:	05 Jan 2023 10:30
Last Modified:	10 Dec 2024 01:13
URI:	https://ueaeprints.uea.ac.uk/id/eprint/90404
DOI:	10.1007/978-3-642-36961-2_12

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