Article

Bidirectional Meta-Kronecker Factored Optimizer and Housdorff Distance Loss for Few-shot Medical Image Segmentation

2022-12-22

Abstract excerpt

To increase the accuracy of medical image analysis using supervised learning-based AI technology, a large amount of accurately labeled training data is required. However, the supervised learning approach may not be applicable to real-world medical imaging due to the lack of labeled data, privacy of patients and the cost of expertise. To handle these issues, we present a bidirectional meta-Kronecker factored optimi...

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Literature Corpus work: 180ce4b0-9f7a-5231-bfac-79ca59b984eb
DOI: 10.21203/rs.3.rs-2324435/v1

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