Review on self supervised learning in medical image analysis
Nowadays, self-supervised learning is a popular method for analysing medical images since it annotates the unstructured data provided and uses these self-generated data labels as a foundation for subsequent model training rounds. This review paper is more focused on the recent research done in medic...
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Published in: | 2023 IEEE 7th Conference on Information and Communication Technology (CICT) pp. 1 - 6 |
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Main Authors: | , |
Format: | Conference Proceeding |
Language: | English |
Published: |
IEEE
15-12-2023
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Subjects: | |
Online Access: | Get full text |
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Summary: | Nowadays, self-supervised learning is a popular method for analysing medical images since it annotates the unstructured data provided and uses these self-generated data labels as a foundation for subsequent model training rounds. This review paper is more focused on the recent research done in medical imaging using self-supervised learning, the major challenges of medical imaging, and the challenges of choosing the proper pretext task and data augmentation while using self-supervised learning. Finally, we address potential approaches for future studies and highlight concerns to consider while developing new self-supervised learning concepts and methodologies. |
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DOI: | 10.1109/CICT59886.2023.10455714 |