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

被引:170
|
作者
Mendrik, Adrienne M. [1 ]
Vincken, Koen L. [1 ]
Kuijf, Hugo J. [1 ]
Breeuwer, Marcel [2 ,3 ]
Bouvy, Willem H. [4 ]
de Bresser, Jeroen [5 ]
Alansary, Amir [6 ]
de Bruijne, Marleen [7 ,8 ,9 ]
Carass, Aaron [10 ]
El-Baz, Ayman [6 ]
Jog, Amod [10 ]
Katyal, Ranveer [11 ]
Khan, Ali R. [12 ,13 ]
van der Lijn, Fedde [7 ,8 ]
Mahmood, Qaiser [14 ]
Mukherjee, Ryan [15 ]
van Opbroek, Annegreet [7 ,8 ]
Paneri, Sahil [11 ]
Pereira, Sergio [16 ]
Persson, Mikael [14 ]
Rajchl, Martin [12 ,17 ]
Sarikaya, Duygu [18 ]
Smedby, Orjan [19 ,20 ,21 ]
Silva, Carlos A. [16 ]
Vrooman, Henri A. [7 ,8 ]
Vyas, Saurabh [15 ]
Wang, Chunliang [19 ,20 ,21 ]
Zhao, Liang [18 ]
Biessels, Geert Jan [4 ]
Viergever, Max A. [1 ]
机构
[1] Univ Med Ctr Utrecht, Image Sci Inst, NL-3584 CX Utrecht, Netherlands
[2] Philips Healthcare, NL-5680 DA Best, Netherlands
[3] Eindhoven Univ Technol, Fac Biomed Engn, NL-5600 MB Eindhoven, Netherlands
[4] Univ Med Ctr Utrecht, Dept Neurol, Brain Ctr Rudolf Magnus, NL-3584 CX Utrecht, Netherlands
[5] Univ Med Ctr Utrecht, Dept Radiol, NL-3584 CX Utrecht, Netherlands
[6] Univ Louisville, Dept Bioengn, BioImaging Lab, Louisville, KY 40292 USA
[7] Erasmus MC, Biomed Imaging Grp Rotterdam, Dept Med Informat, NL-3015 CN Rotterdam, Netherlands
[8] Erasmus MC, Dept Radiol, NL-3015 CN Rotterdam, Netherlands
[9] Univ Copenhagen, Dept Comp Sci, DK-2100 Copenhagen, Denmark
[10] Johns Hopkins Univ, Dept Elect & Comp Engn, Image Anal & Commun Lab, Baltimore, MD 21218 USA
[11] LNM Inst Informat Technol, Dept Elect & Commun Engn, Jaipur 302031, Rajasthan, India
[12] Robarts Res Inst, Imaging Labs, London, ON N6A 5B7, Canada
[13] Univ Western Ontario, Dept Med Biophys, London, ON N6A 3K7, Canada
[14] Chalmers Univ Technol, Signals & Syst, S-41296 Gothenburg, Sweden
[15] Johns Hopkins Univ, Appl Phys Lab, Laurel, MD 20723 USA
[16] Univ Minho, Dept Elect, P-4800058 Guimaraes, Portugal
[17] Univ London Imperial Coll Sci Technol & Med, Dept Comp, London SW7 2AZ, England
[18] SUNY Buffalo, Dept Comp Sci & Engn, Buffalo, NY 14260 USA
[19] Linkoping Univ, Ctr Med Imaging Sci & Visualizat, S-58185 Linkoping, Sweden
[20] Linkoping Univ, Dept Radiol, S-58185 Linkoping, Sweden
[21] Linkoping Univ, Dept Med & Hlth Sci, S-58185 Linkoping, Sweden
关键词
SURFACE-BASED ANALYSIS; PATTERN-RECOGNITION; TISSUE; VOLUMES; ALGORITHMS;
D O I
10.1155/2015/813696
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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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页数:16
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