CryptoDL: Predicting Dyslexia Biomarkers from Encrypted Neuroimaging Dataset Using Energy-Efficient Residue Number System and Deep Convolutional Neural Network
The increasing availability of medical images generated via different imaging techniques necessitates the need for their remote analysis and diagnosis, especially when such datasets involve brain morphological biomarkers, an important biological symmetry concept. This development has made the privac...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-05-01
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| Series: | Symmetry |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-8994/12/5/836 |