Imperial College London

ProfessorDanielRueckert

Faculty of EngineeringDepartment of Computing

Head of Department of Computing
 
 
 
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Contact

 

+44 (0)20 7594 8333d.rueckert Website

 
 
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Location

 

568Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Gousias:2012:10.1109/IST.2012.6295511,
author = {Gousias, IS and Hammers, A and Counsell, SJ and Edwards, AD and Rueckert, D},
doi = {10.1109/IST.2012.6295511},
pages = {95--100},
title = {Automatic segmentation of pediatric brain MRIs using a maximum probability pediatric atlas},
url = {http://dx.doi.org/10.1109/IST.2012.6295511},
year = {2012}
}

RIS format (EndNote, RefMan)

TY  - CPAPER
AB - 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. © 2012 IEEE.
AU - Gousias,IS
AU - Hammers,A
AU - Counsell,SJ
AU - Edwards,AD
AU - Rueckert,D
DO - 10.1109/IST.2012.6295511
EP - 100
PY - 2012///
SP - 95
TI - Automatic segmentation of pediatric brain MRIs using a maximum probability pediatric atlas
UR - http://dx.doi.org/10.1109/IST.2012.6295511
ER -