Article detail · 2015
The Multimodal Brain Tumor Image Segmentation Benchmark BRATS
- Year
- 2015
- Type
- article
Data source split
- YÖKSİS YÖKSİS article record
- YÖKSİS venue IEEE Transactions on Medical Imaging
- Catalog match (ISSN) IEEE Transactions on Medical Imaging
- OpenAlex OpenAlex enrichment (abstract, citations, topics)
Abstract
OpenAlex · English
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 sub-regions 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.
Topics
Citations
OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.
6,800 citations
OpenAlex cited_by_count (cache / database)
105 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).
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