@inproceedings{6a35e329a1d544948553d3aa2368c4e3,
title = "Automatic segmentation of pediatric brain MRIs using a maximum probability pediatric atlas",
abstract = "Automatic anatomical segmentation of pediatric brain MR data sets can be pursued with the use of registration algorithms when segmentation priors (atlases) are in hand. We investigated the performance of a maximum probability pediatric atlas (MPPA), template based registration and label propagation. The MPPA was created from the 33 pediatric data sets, available through www.brain-development.org. We evaluated the performance of the MPPA comparing with manual segmentations by means of the Dice overlap coefficient. Dice values, averaged across representative regions, were 0.90 ± 0.03 for the hippocampus, 0.92 ± 0.01 for the caudate nucleus and 0.92 ± 0.02 for the pre-central gyrus. Segmentations of 36 further unsegmented target 3T images (1-year-olds and 2-year-olds) yielded visibly high-quality results. This registration approach allows the rapid construction of automatically labeled pediatric brain atlases in a single registration step.",
keywords = "Pediatric brain atlasing, brain atlases, brain segmentation, non-rigid registration, parameters, priors, validation",
author = "Gousias, {Ioannis S.} and Alexander Hammers and Counsell, {Serena J.} and Edwards, {A. David} and Daniel Rueckert",
year = "2012",
doi = "10.1109/IST.2012.6295511",
language = "English",
isbn = "9781457717741",
series = "IST 2012 - 2012 IEEE International Conference on Imaging Systems and Techniques, Proceedings",
pages = "95--100",
booktitle = "IST 2012 - 2012 IEEE International Conference on Imaging Systems and Techniques, Proceedings",
note = "2012 IEEE International Conference on Imaging Systems and Techniques, IST 2012 ; Conference date: 16-07-2012 Through 17-07-2012",
}