ANODE09 is an initiative to compare systems that perform automatic detection of pulmonary nodules in chest CT scans on a single common database, with a single evaluation protocol.
LUNA16
Challenge
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The LUNA16 challenge: automatic nodule detection on chest CT
Decathlon
Challenge
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The Medical Segmentation Decathlon challenge tests the generalisability of machine learning algorithms when applied to 10 different semantic segmentation task.
TIGER
Challenge
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Grand challenge on automate assessment of tumor infiltrating lymphocytes in digital pathology slides of triple negative and Her2-positive breast cancers
The PI-CAI Challenge
Challenge
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Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI
TDSC-ABUS2023
Challenge
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Tumor Detection, Segmentation and Classification Challenge on Automated 3D Breast Ultrasound
BCNB
Challenge
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Early Breast Cancer Core-Needle Biopsy WSI Dataset
MICCAI FLARE 2022
Challenge
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MICCAI 2022 Fast and Low-resource semi-supervised Abdominal oRgan sEgmentation (FLARE) Challenge
autoPET
Challenge
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Automatic lesion segmentation in whole-body FDG-PET/CT
ACROBAT 2023
Challenge
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The ACROBAT challenge aims to advance the development of WSI registration algorithms that can align WSIs of IHC-stained breast cancer tissue sections to corresponding tissue regions that were stained with H&E. All WSIs originate from routine diagnostic workflows.
