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

作者：Mendrik Adrienne 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 Sergio; Persson Mikael; Rajchl Martin; Sarikaya Duygu; Smedby Orjan; Silva Carlos A; Vrooman Henri A; Vyas Saurabh; Wang Chunliang; Zhao Liang; Biessels Geert Jan

来源：Computational Intelligence and Neuroscience, 2015, 2015: 813696.

DOI：10.1155/2015/813696

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.

• 出版日期2015