The Multimodal Brain TumorImage Segmentation Benchmark (BRATS)

Menze, Bjoern; Reyes, Mauricio; Van Leemput, Koen; Porz, Nicole; Wiest, Roland (2015). The Multimodal Brain TumorImage Segmentation Benchmark (BRATS). IEEE transactions on medical imaging, 34(10), pp. 199-2024. Institute of Electrical and Electronics Engineers IEEE 10.1109/TMI.2014.2377694

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In this paper we report the set-up and results of the Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) organized in conjunction with the MICCAI 2012 and 2013 conferences. Twenty state-of-the-art tumor segmentation algorithms were applied to a set of 65 multi-contrast MR scans of low- and high-grade glioma patients - manually annotated by up to four raters - and to 65 comparable scans generated using tumor image simulation software. Quantitative evaluations revealed considerable disagreement between the human raters in segmenting various tumor sub-regions (Dice scores in the range 74-85%), illustrating the difficulty of this task. We found that different algorithms worked best for different sub-regions (reaching performance comparable to human inter-rater variability), but that no single algorithm ranked in the top for all subregions simultaneously. Fusing several good algorithms using a hierarchical majority vote yielded segmentations that consistently ranked above all individual algorithms, indicating remaining opportunities for further methodological improvements. The BRATS image data and manual annotations continue to be publicly available through an online evaluation system as an ongoing benchmarking resource.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute for Surgical Technology & Biomechanics ISTB
04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Neurosurgery
04 Faculty of Medicine > Department of Radiology, Neuroradiology and Nuclear Medicine (DRNN) > Institute of Diagnostic and Interventional Neuroradiology

UniBE Contributor:

Reyes, Mauricio; Porz, Nicole and Wiest, Roland

Subjects:

500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health

ISSN:

0278-0062

Publisher:

Institute of Electrical and Electronics Engineers IEEE

Language:

English

Submitter:

Nicole Söll

Date Deposited:

16 Mar 2015 10:58

Last Modified:

10 May 2016 15:27

Publisher DOI:

10.1109/TMI.2014.2377694

PubMed ID:

25494501

BORIS DOI:

10.7892/boris.64551

URI:

https://boris.unibe.ch/id/eprint/64551

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