computer-vision-11
Tumor Segmentation
3260 papers • 126 benchmarks • 313 datasets
Tumor Segmentation is the task of identifying the spatial location of a tumor. It is a pixel-level prediction where each pixel is classified as a tumor or background. The most popular benchmark for this task is the BraTS dataset. The models are typically evaluated with the Dice Score metric.
(Image credit: Papersgraph)
Benchmarks
These leaderboards are used to track progress in tumor-segmentation-11
Trend
Dataset
Best Model
Actions
BUS 2017 Dataset B
BUS 2017 Dataset B
DigestPath
DigestPath
LiTS17
LiTS17
Libraries
iUse these libraries to find tumor-segmentation-11 models and implementations
3 papers 1,989
Datasets
Subtasks
No subtasks available.