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MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans
University of Medical Centre Utrecht, Netherlands.
University of Medical Centre Utrecht, Netherlands.
University of Medical Centre Utrecht, Netherlands.
Philips Healthcare, Netherlands; Eindhoven University of Technology, Netherlands.
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2015 (English)In: Computational Intelligence and Neuroscience, ISSN 1687-5265, E-ISSN 1687-5273, 813696Article in journal (Refereed) PublishedText
Abstract [en]

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.

Place, publisher, year, edition, pages
Hindawi Publishing Corporation, 2015. 813696
National Category
Clinical Medicine
URN: urn:nbn:se:liu:diva-123844DOI: 10.1155/2015/813696ISI: 000366408500001PubMedID: 26759553OAI: diva2:892847

Funding Agencies|IMDI from ZonMw [104002002]; Netherlands Organisation for Health Research and Development - Philips; University Medical Center Utrecht; Eindhoven University of Technology; VIDI from ZonMw [91711384]; Netherlands Heart Foundation [2010T073]; University Medical Center Utrecht (Netherlands); NWO (the Netherlands Organisation for Scientific Research); NIH [1 R21CA160825-01]; China Scholarship Council (CSC)

Available from: 2016-01-11 Created: 2016-01-11 Last updated: 2016-02-04Bibliographically approved

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Smedby, ÖrjanWang, Chunliang
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Division of Radiological SciencesFaculty of Medicine and Health SciencesDepartment of Radiology in LinköpingCenter for Medical Image Science and Visualization (CMIV)
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Computational Intelligence and Neuroscience
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