Matches in SemOpenAlex for { <https://semopenalex.org/work/W4384828685> ?p ?o ?g. }
- W4384828685 endingPage "8295" @default.
- W4384828685 startingPage "8295" @default.
- W4384828685 abstract "Electronic health records (EHRs) security is a critical challenge in the implementation and administration of Internet of Medical Things (IoMT) systems within the healthcare sector’s heterogeneous environment. As digital transformation continues to advance, ensuring privacy, integrity, and availability of EHRs become increasingly complex. Various imaging modalities, including PET, MRI, ultrasonography, CT, and X-ray imaging, play vital roles in medical diagnosis, allowing healthcare professionals to visualize and assess the internal structures, functions, and abnormalities within the human body. These diagnostic images are typically stored, shared, and processed for various purposes, including segmentation, feature selection, and image denoising. Cryptography techniques offer a promising solution for protecting sensitive medical image data during storage and transmission. Deep learning has the potential to revolutionize cryptography techniques for securing medical images. This paper explores the application of deep learning techniques in medical image cryptography, aiming to enhance the privacy and security of healthcare data. It investigates the use of deep learning models for image encryption, image resolution enhancement, detection and classification, encrypted compression, key generation, and end-to-end encryption. Finally, we provide insights into the current research challenges and promising directions for future research in the field of deep learning applications in medical image cryptography." @default.
- W4384828685 created "2023-07-21" @default.
- W4384828685 creator A5014288820 @default.
- W4384828685 creator A5060684252 @default.
- W4384828685 date "2023-07-18" @default.
- W4384828685 modified "2023-10-11" @default.
- W4384828685 title "Deep Learning for Medical Image Cryptography: A Comprehensive Review" @default.
- W4384828685 cites W1641498739 @default.
- W4384828685 cites W2051267297 @default.
- W4384828685 cites W2145764948 @default.
- W4384828685 cites W2180612164 @default.
- W4384828685 cites W2183341477 @default.
- W4384828685 cites W2194775991 @default.
- W4384828685 cites W2253429366 @default.
- W4384828685 cites W2412782625 @default.
- W4384828685 cites W2499316477 @default.
- W4384828685 cites W2529153069 @default.
- W4384828685 cites W2533800772 @default.
- W4384828685 cites W2543927648 @default.
- W4384828685 cites W2559597482 @default.
- W4384828685 cites W2580596898 @default.
- W4384828685 cites W2584017349 @default.
- W4384828685 cites W2592929672 @default.
- W4384828685 cites W2613041730 @default.
- W4384828685 cites W2618530766 @default.
- W4384828685 cites W2724710774 @default.
- W4384828685 cites W2768338208 @default.
- W4384828685 cites W2800012666 @default.
- W4384828685 cites W2807189427 @default.
- W4384828685 cites W2828862258 @default.
- W4384828685 cites W2900443369 @default.
- W4384828685 cites W2903117925 @default.
- W4384828685 cites W2921008479 @default.
- W4384828685 cites W2922384037 @default.
- W4384828685 cites W2924551358 @default.
- W4384828685 cites W2947263797 @default.
- W4384828685 cites W2953914369 @default.
- W4384828685 cites W2963857521 @default.
- W4384828685 cites W2963881378 @default.
- W4384828685 cites W2964056778 @default.
- W4384828685 cites W2964350391 @default.
- W4384828685 cites W2969281952 @default.
- W4384828685 cites W2977942577 @default.
- W4384828685 cites W2979646594 @default.
- W4384828685 cites W2980189697 @default.
- W4384828685 cites W2987609860 @default.
- W4384828685 cites W2988468782 @default.
- W4384828685 cites W3000028066 @default.
- W4384828685 cites W3001152983 @default.
- W4384828685 cites W3007943565 @default.
- W4384828685 cites W3014047622 @default.
- W4384828685 cites W3021182036 @default.
- W4384828685 cites W3023836269 @default.
- W4384828685 cites W3026796362 @default.
- W4384828685 cites W3028201343 @default.
- W4384828685 cites W3033046693 @default.
- W4384828685 cites W3033511014 @default.
- W4384828685 cites W3035751626 @default.
- W4384828685 cites W3040298941 @default.
- W4384828685 cites W3042445013 @default.
- W4384828685 cites W3046108963 @default.
- W4384828685 cites W3080400611 @default.
- W4384828685 cites W3095681026 @default.
- W4384828685 cites W3101156210 @default.
- W4384828685 cites W3101294892 @default.
- W4384828685 cites W3105081694 @default.
- W4384828685 cites W3107451140 @default.
- W4384828685 cites W3107645027 @default.
- W4384828685 cites W3113259356 @default.
- W4384828685 cites W3113541070 @default.
- W4384828685 cites W3123982987 @default.
- W4384828685 cites W3125985750 @default.
- W4384828685 cites W3127426043 @default.
- W4384828685 cites W3129501281 @default.
- W4384828685 cites W3131326546 @default.
- W4384828685 cites W3133661165 @default.
- W4384828685 cites W3134130140 @default.
- W4384828685 cites W3138986594 @default.
- W4384828685 cites W3148831051 @default.
- W4384828685 cites W3152813604 @default.
- W4384828685 cites W3162744106 @default.
- W4384828685 cites W3163936961 @default.
- W4384828685 cites W3164581645 @default.
- W4384828685 cites W3184133302 @default.
- W4384828685 cites W3192911000 @default.
- W4384828685 cites W3197780267 @default.
- W4384828685 cites W3206966550 @default.
- W4384828685 cites W3214926239 @default.
- W4384828685 cites W4206615250 @default.
- W4384828685 cites W4206693420 @default.
- W4384828685 cites W4221027618 @default.
- W4384828685 cites W4221065228 @default.
- W4384828685 cites W4224308162 @default.
- W4384828685 cites W4225339296 @default.
- W4384828685 cites W4225377307 @default.
- W4384828685 cites W4285006260 @default.
- W4384828685 cites W4288436642 @default.
- W4384828685 cites W4289792991 @default.