Secure management of retinal imaging based on deep learning, zero-watermarking and reversible data hiding-Reference-Cited by-同舟云学术

Secure management of retinal imaging based on deep learning, zero-watermarking and reversible data hiding

Published:2023-01-24 Issue:1 Volume:40 Page:245-260
ISSN:0178-2789
Container-title:The Visual Computer
language:en
Short-container-title:Vis Comput

Author:

Garcia-Nonoal Zaira^ORCID,Mata-Mendoza David^ORCID,Cedillo-Hernandez Manuel^ORCID,Nakano-Miyatake Mariko^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Software

Link

https://link.springer.com/content/pdf/10.1007/s00371-023-02778-1.pdf

Reference40 articles.

1. Shi, C., Lee, J., Wang, G., et al.: Assessment of image quality on color fundus retinal images using the automatic retinal image analysis. Sci. Rep. 12, 10455 (2022). https://doi.org/10.1038/s41598-022-13919-2

2. Nelson, S.E., Steuernagle, J., Rotello, L., et al.: COVID-19 and telehealth in the intensive care unit setting: a survey. BMC Health Serv. Res. 22, 797 (2022). https://doi.org/10.1186/s12913-022-08197-7

3. National Electrical Manufacturers Association (NEMA), DICOM Security. p. 1. [Online] 13 Jan 2023. Available at: https://www.dicomstandard.org/using/security/

4. Mahesh Selvi, T., Kavitha, V.: A privacy-aware deep learning framework for health recommendation system on analysis of big data. Vis. Comput. (2021). https://doi.org/10.1007/s00371-020-02021-1

5. Qasim, A.F., Meziane, F., Aspin, R.: Digital watermarking: applicability for developing trust in medical imaging workflows state of the art review. Comput. Sci. Rev. 27, 45–60 (2018). https://doi.org/10.1016/j.cosrev.2017.11.003

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