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Found 2 papers, 1 papers with code
Guidelines for Cerebrovascular Segmentation: Managing Imperfect Annotations in the context of Semi-Supervised Learning
Based on these experiments, we provide guidelines for the annotation and training of cerebrovascular segmentation models.
Cascaded multitask U-Net using topological loss for vessel segmentation and centerline extraction
To overcome these limitations, the clDice loss, a topological loss that focuses on the vessel centerlines, has been recently proposed.
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