Diegif: An efficient and secured DICOM to EGIF conversion framework for confidentiality in machine learning training
Medical imaging plays a critical role in contemporary healthcare, although it confronts issues relating to storage, security, and confidentiality in machine learning-based diagnostic systems. The proposed framework, Diegif, presents an efficient and safe mechanism for converting DICOM (Digital Imagi...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
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| Series: | Results in Control and Optimization |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666720725000013 |
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