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  4. Evaluation of automatic neonatal brain segmentation algorithms: The NeoBrainS12 challenge
 
research article

Evaluation of automatic neonatal brain segmentation algorithms: The NeoBrainS12 challenge

Isgum, Ivana
•
J.N.L. Benders, Manon
•
Avants, Brian
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February 2015
Medical Image Analysis

A number of algorithms for brain segmentation in preterm born infants have been published, but a reliable comparison of their performance is lacking. The NeoBrainS12 study (http://neobrains12.isi.uu.nl), providing three different image sets of preterm born infants, was set up to provide such a comparison. These sets are (i) axial scans acquired at 40 weeks corrected age, (ii) coronal scans acquired at 30 weeks corrected age and (iii) coronal scans acquired at 40 weeks corrected age. Each of these three sets consists of three T1- and T2-weighted MR images of the brain acquired with a 3T MRI scanner. The task was to segment cortical grey matter, non-myelinated and myelinated white matter, brainstem, basal ganglia and thalami, cerebellum, and cerebrospinal fluid in the ventricles and in the extracerebral space separately. Any team could upload the results and all segmentations were evaluated in the same way. This paper presents the results of eight participating teams. The results demonstrate that the participating methods were able to segment all tissue classes well, except myelinated white matter.

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Type
research article
DOI
10.1016/j.media.2014.11.001
Web of Science ID

WOS:000349592000010

Author(s)
Isgum, Ivana
J.N.L. Benders, Manon
Avants, Brian
Cardoso, M. Jorge
Counsell, Serena J.
Fischi Gomez, Elda  
Gui, Laura
Hüppi, Petra S.
Kersbergen, Karina
Makropoulos, Antonios
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Date Issued

2015-02

Publisher

Elsevier Science Bv

Published in
Medical Image Analysis
Volume

20

Issue

1

Start page

135

End page

151

Subjects

Neonatal brain

•

MRI

•

Brain segmentation

•

Segmentation evaluation

•

Segmentation comparison

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LTS5  
Available on Infoscience
January 5, 2015
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/109889
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