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MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans

Many methods have been proposed for tissue segmentation in brain MRI scans. The multitude of methods proposed complicates the choice of one method above others. We have therefore established the MRBrainS online evaluation framework for evaluating (semi)automatic algorithms that segment gray matter (...

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Autores principales: Mendrik, Adriënne M., Vincken, Koen L., Kuijf, Hugo J., Breeuwer, Marcel, Bouvy, Willem H., de Bresser, Jeroen, Alansary, Amir, de Bruijne, Marleen, Carass, Aaron, El-Baz, Ayman, Jog, Amod, Katyal, Ranveer, Khan, Ali R., van der Lijn, Fedde, Mahmood, Qaiser, Mukherjee, Ryan, van Opbroek, Annegreet, Paneri, Sahil, Pereira, Sérgio, Persson, Mikael, Rajchl, Martin, Sarikaya, Duygu, Smedby, Örjan, Silva, Carlos A., Vrooman, Henri A., Vyas, Saurabh, Wang, Chunliang, Zhao, Liang, Biessels, Geert Jan, Viergever, Max A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4680055/
https://www.ncbi.nlm.nih.gov/pubmed/26759553
http://dx.doi.org/10.1155/2015/813696
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author Mendrik, Adriënne M.
Vincken, Koen L.
Kuijf, Hugo J.
Breeuwer, Marcel
Bouvy, Willem H.
de Bresser, Jeroen
Alansary, Amir
de Bruijne, Marleen
Carass, Aaron
El-Baz, Ayman
Jog, Amod
Katyal, Ranveer
Khan, Ali R.
van der Lijn, Fedde
Mahmood, Qaiser
Mukherjee, Ryan
van Opbroek, Annegreet
Paneri, Sahil
Pereira, Sérgio
Persson, Mikael
Rajchl, Martin
Sarikaya, Duygu
Smedby, Örjan
Silva, Carlos A.
Vrooman, Henri A.
Vyas, Saurabh
Wang, Chunliang
Zhao, Liang
Biessels, Geert Jan
Viergever, Max A.
author_facet Mendrik, Adriënne M.
Vincken, Koen L.
Kuijf, Hugo J.
Breeuwer, Marcel
Bouvy, Willem H.
de Bresser, Jeroen
Alansary, Amir
de Bruijne, Marleen
Carass, Aaron
El-Baz, Ayman
Jog, Amod
Katyal, Ranveer
Khan, Ali R.
van der Lijn, Fedde
Mahmood, Qaiser
Mukherjee, Ryan
van Opbroek, Annegreet
Paneri, Sahil
Pereira, Sérgio
Persson, Mikael
Rajchl, Martin
Sarikaya, Duygu
Smedby, Örjan
Silva, Carlos A.
Vrooman, Henri A.
Vyas, Saurabh
Wang, Chunliang
Zhao, Liang
Biessels, Geert Jan
Viergever, Max A.
author_sort Mendrik, Adriënne M.
collection PubMed
description Many methods have been proposed for tissue segmentation in brain MRI scans. The multitude of methods proposed complicates the choice of one method above others. We have therefore established the MRBrainS online evaluation framework for evaluating (semi)automatic algorithms that segment gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) on 3T brain MRI scans of elderly subjects (65–80 y). Participants apply their algorithms to the provided data, after which their results are evaluated and ranked. Full manual segmentations of GM, WM, and CSF are available for all scans and used as the reference standard. Five datasets are provided for training and fifteen for testing. The evaluated methods are ranked based on their overall performance to segment GM, WM, and CSF and evaluated using three evaluation metrics (Dice, H95, and AVD) and the results are published on the MRBrainS13 website. We present the results of eleven segmentation algorithms that participated in the MRBrainS13 challenge workshop at MICCAI, where the framework was launched, and three commonly used freeware packages: FreeSurfer, FSL, and SPM. The MRBrainS evaluation framework provides an objective and direct comparison of all evaluated algorithms and can aid in selecting the best performing method for the segmentation goal at hand.
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spelling pubmed-46800552016-01-12 MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans Mendrik, Adriënne M. Vincken, Koen L. Kuijf, Hugo J. Breeuwer, Marcel Bouvy, Willem H. de Bresser, Jeroen Alansary, Amir de Bruijne, Marleen Carass, Aaron El-Baz, Ayman Jog, Amod Katyal, Ranveer Khan, Ali R. van der Lijn, Fedde Mahmood, Qaiser Mukherjee, Ryan van Opbroek, Annegreet Paneri, Sahil Pereira, Sérgio Persson, Mikael Rajchl, Martin Sarikaya, Duygu Smedby, Örjan Silva, Carlos A. Vrooman, Henri A. Vyas, Saurabh Wang, Chunliang Zhao, Liang Biessels, Geert Jan Viergever, Max A. Comput Intell Neurosci Research Article Many methods have been proposed for tissue segmentation in brain MRI scans. The multitude of methods proposed complicates the choice of one method above others. We have therefore established the MRBrainS online evaluation framework for evaluating (semi)automatic algorithms that segment gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) on 3T brain MRI scans of elderly subjects (65–80 y). Participants apply their algorithms to the provided data, after which their results are evaluated and ranked. Full manual segmentations of GM, WM, and CSF are available for all scans and used as the reference standard. Five datasets are provided for training and fifteen for testing. The evaluated methods are ranked based on their overall performance to segment GM, WM, and CSF and evaluated using three evaluation metrics (Dice, H95, and AVD) and the results are published on the MRBrainS13 website. We present the results of eleven segmentation algorithms that participated in the MRBrainS13 challenge workshop at MICCAI, where the framework was launched, and three commonly used freeware packages: FreeSurfer, FSL, and SPM. The MRBrainS evaluation framework provides an objective and direct comparison of all evaluated algorithms and can aid in selecting the best performing method for the segmentation goal at hand. Hindawi Publishing Corporation 2015 2015-12-02 /pmc/articles/PMC4680055/ /pubmed/26759553 http://dx.doi.org/10.1155/2015/813696 Text en Copyright © 2015 Adriënne M. Mendrik et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Mendrik, Adriënne M.
Vincken, Koen L.
Kuijf, Hugo J.
Breeuwer, Marcel
Bouvy, Willem H.
de Bresser, Jeroen
Alansary, Amir
de Bruijne, Marleen
Carass, Aaron
El-Baz, Ayman
Jog, Amod
Katyal, Ranveer
Khan, Ali R.
van der Lijn, Fedde
Mahmood, Qaiser
Mukherjee, Ryan
van Opbroek, Annegreet
Paneri, Sahil
Pereira, Sérgio
Persson, Mikael
Rajchl, Martin
Sarikaya, Duygu
Smedby, Örjan
Silva, Carlos A.
Vrooman, Henri A.
Vyas, Saurabh
Wang, Chunliang
Zhao, Liang
Biessels, Geert Jan
Viergever, Max A.
MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans
title MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans
title_full MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans
title_fullStr MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans
title_full_unstemmed MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans
title_short MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans
title_sort mrbrains challenge: online evaluation framework for brain image segmentation in 3t mri scans
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4680055/
https://www.ncbi.nlm.nih.gov/pubmed/26759553
http://dx.doi.org/10.1155/2015/813696
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