Advances, Systems and Applications
Table 2 Comparison of existing implementations and proposed work
From: Securing medical image privacy in cloud using deep learning network
REFERENCE | DATASET | MODEL | STATISTICAL EVALUATIONS |
|---|---|---|---|
Cui et al., (2019) [10] | Ga-PRGD2 PET/CT | Deep Decoder | CNR = 53.35% ± 21.78% |
Y. Zheng et al., (2021) [5] | Real time CHEST X-Rays | Deep Neural Network | SSIM = 0.002 |
Y. Zheng et al., (2017) [29] | Berkeley dataset4 | SSE-LSH symmetric encryption | SNR = 0.179db, SSIM = 0.004 |
Proposed work | Real time CT images | Pseudo-Predictive deep Denoising network | SNR = 24.31625, SI = 0.973, ER = 0.001, CNR = 42.2% ± 15.44% |