Challenge on medical image registration addressing: learning from small datasets; estimating large deformations; dealing with multi-modal scans; and learning from noisy annotations
Ultra-low Dose PET Imaging Challenge
Challenge
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This challenge aims to develop deep learning algorithms capable of recovering high-quality imaging from low-dose scans on this ultra-low-dose PET scanner.
MICCAI HECKTOR 2022
Challenge
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Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT Images
SegRap 2023
Challenge
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A segmentation challenge with 200 patients (two modalities of CT images, 45 OARs and 2 GTVs).
