LiTS17 is a liver tumor segmentation benchmark. The data and segmentations are provided by various clinical sites around the world.
39 PAPERS • 3 BENCHMARKS
BRATS 2014 is a brain tumor segmentation dataset.
5 PAPERS • 1 BENCHMARK
The BraTS 2015 dataset is a dataset for brain tumor image segmentation. It consists of 220 high grade gliomas (HGG) and 54 low grade gliomas (LGG) MRIs. Segmented “ground truth” is provide about four intra-tumoral classes, viz. edema, enhancing tumor, non-enhancing tumor, and necrosis.
66 PAPERS • 1 BENCHMARK
BRATS 2016 is a brain tumor segmentation dataset. It shares the same training set as BRATS 2015, which consists of 220 HHG and 54 LGG. Its testing dataset consists of 191 cases with unknown grades.
13 PAPERS • NO BENCHMARKS YET
Introduced by Da et al. in DigestPath: a Benchmark Dataset with Challenge Review for the Pathological Detection and Segmentation of Digestive-System Grand-Challenge Page 1. Colonoscopy tissue segment dataset Colonoscopy pathology examination can find cells of early-stage colon tumor from small tissue slices. Here we propose a challenge task on automatic colonoscopy tissue segmentation and screening, aiming at automatic lesion segmentation and classification of the whole tissue (benign vs. malignant). DigestPath: a Benchmark Dataset with Challenge Review for the Pathological Detection and Segmentation of Digestive-System[J]. Medical Image Analysis, 2022: 102485.
22 PAPERS • 1 BENCHMARK
…The dataset comprises Computed Tomography (CT), Positron Emission Tomography (PET)/CT images, semantic annotations of the tumors as observed on the medical images using a controlled vocabulary, segmentation
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