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Deep learning-based group-wise registration for longitudinal MRI analysis in glioma
The proposed methods may serve as an alternative to classical toolboxes, to provide further insight into glioma growth.
Towards continuous learning for glioma segmentation with elastic weight consolidation
When finetuning a convolutional neural network (CNN) on data from a new domain, catastrophic forgetting will reduce performance on the original training data.
Multi-modal segmentation with missing MR sequences using pre-trained fusion networks
Missing data is a common problem in machine learning and in retrospective imaging research it is often encountered in the form of missing imaging modalities.
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