Deep Learning for Medical Image Cryptography: A Comprehensive Review

Electronic health records (EHRs) security is a critical challenge in the implementation and administration of Internet Medical Things (IoMT) systems within healthcare sector’s heterogeneous environment. As digital transformation continues to advance, ensuring privacy, integrity, availability EHRs become increasingly complex. Various imaging modalities, including PET, MRI, ultrasonography, CT, X-ray imaging, play vital roles medical diagnosis, allowing professionals visualize assess internal structures, functions, abnormalities human body. These diagnostic images are typically stored, shared, processed for various purposes, segmentation, feature selection, image denoising. Cryptography techniques offer promising solution protecting sensitive data during storage transmission. Deep learning has potential revolutionize cryptography securing images. This paper explores application deep cryptography, aiming enhance privacy data. It investigates use models encryption, resolution enhancement, detection classification, encrypted compression, key generation, end-to-end encryption. Finally, we provide insights into current research challenges directions future field applications cryptography.