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Found 2 papers, 1 papers with code
Leveraging Old Knowledge to Continually Learn New Classes in Medical Images
Class-incremental continual learning is a core step towards developing artificial intelligence systems that can continuously adapt to changes in the environment by learning new concepts without forgetting those previously learned.
AIRNet: Self-Supervised Affine Registration for 3D Medical Images using Neural Networks
Our proposed method was evaluated on magnetic resonance images of the axial view of human brain and compared with the performance of a conventional image registration method.
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