The VESSEL12 challenge compares methods for automatic (and semi-automatic) segmentation of blood vessels in the lungs from CT images.
PROMISE12
Challenge
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The goal of this challenge is to compare interactive and (semi)-automatic segmentation algorithms for MRI of the prostate.
ICIAR 2018
Challenge
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Can you develop a method for automatic detection of cancerous regions in breast cancer histology images?
SLIVER07
Challenge
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The goal of this competition is to compare different algorithms to segment the liver from clinical 3D computed tomography (CT) scans.
HC18
Challenge
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Automated measurement of fetal head circumference using 2D ultrasound images
ANHIR
Challenge
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The challenge focuses on comparing the accuracy (using manually annotated landmarks) and the approximate speed of automatic non-linear registration methods for aligning microscopy images of multi-stained histology tissue samples.
CHAOS
Challenge
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In this challenge, you segment the liver in CT data, and segment liver, spleen, and kidneys in MRI data.
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.
VerSe`19
Challenge
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Vertebrae labelling and segmentation on a spine dataset on an unprecedented 150 CT scans with voxel-level vertebral annotations.
LNDb Challenge
Challenge
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Lung cancer screening and Fleischner follow-up determination in chest CT through nodule detection, segmentation and characterization
QUBIQ
Challenge
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Quantification of Uncertainties in Biomedical Image Segmentation Challenge
LoDoPaB-CT
Challenge
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Low-Dose CT reconstruction in the setting of the LoDoPaB-CT dataset.
Where is VALDO?
Challenge
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Vascular Lesion Detection Challenge at MICCAI 2021
SegPC-2021
Challenge
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This challenge is positioned towards robust segmentation of cells which is the first stage to build such a tool for plasma cell cancer, namely, Multiple Myeloma (MM), which is a type of blood cancer.
