TY - JOUR
T1 - Evaluation of automatic neonatal brain segmentation algorithms: The NeoBrainS12 challenge
AU - Išgum, Ivana
AU - Benders, Manon J. N. L.
AU - Avants, Brian
AU - Cardoso, M. Jorge
AU - Counsell, Serena J.
AU - Gomez, Elda Fischi
AU - Gui, Laura
AU - Huppi, Petra S.
AU - Kersbergen, Karina J.
AU - Makropoulos, Antonios
AU - Melbourne, Andrew
AU - Moeskops, Pim
AU - Mol, Christian P.
AU - Kuklisova-Murgasova, Maria
AU - Rueckert, Daniel
AU - Schnabel, Julia A.
AU - Srhoj-Egekher, Vedran
AU - Wu, Jue
AU - Wang, Siying
AU - de Vries, Linda S.
AU - Viergever, Max A.
PY - 2015
Y1 - 2015
N2 - 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.
AB - 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.
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84920895738&origin=inward
UR - https://www.ncbi.nlm.nih.gov/pubmed/25487610
U2 - https://doi.org/10.1016/j.media.2014.11.001
DO - https://doi.org/10.1016/j.media.2014.11.001
M3 - Article
C2 - 25487610
SN - 1361-8415
VL - 20
SP - 135
EP - 151
JO - Medical Image Analysis
JF - Medical Image Analysis
IS - 1
ER -