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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Bibliographic Details

Published in:	Results in Control and Optimization
Main Authors:	Abdullah Al Siam, Md Maruf Hassan, Md Atikur Rahaman, Masuk Abdullah
Format:	Article
Language:	English
Published:	Elsevier 2025-03-01
Subjects:	DICOM EGIF ML AES Encryption Decryption
Online Access:	http://www.sciencedirect.com/science/article/pii/S2666720725000013