![]() ![]() In current clinical routine, as well as in clinical studies, the resulting images are evaluated either based on qualitative criteria only (indicating, for example, the presence of characteristic hyper-intense tissue appearance in contrast-enhanced T1-weighted MRI), or by relying on such rudimentary quantitative measures as the largest diameter visible from axial images of the lesion. For both groups, intensive neuroimaging protocols are used before and after treatment to evaluate the progression of the disease and the success of a chosen treatment strategy. The slower growing low-grade variants, such as low-grade astrocytomas or oligodendrogliomas, come with a life expectancy of several years so aggressive treatment is often delayed as long as possible. ![]() The clinical population with the more aggressive form of the disease, classified as high-grade gliomas, have a median survival rate of two years or less and require immediate treatment. Despite considerable advances in glioma research, patient diagnosis remains poor. Gliomas are the most frequent primary brain tumors in adults, presumably originating from glial cells and infiltrating the surrounding tissues. The BRATS image data and manual annotations continue to be publicly available through an online evaluation system as an ongoing benchmarking resource. 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. 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. 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. 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. ![]() 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 20 conferences. ![]()
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December 2022
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