SDCA: a novel stack deep convolutional autoencoder – an application on retinal image denoising

Retinal fundus images are used for the diagnosis and treatment of various eye diseases such as diabetic retinopathy, glaucoma, exudates and so on. The retinal vasculature is difficult to investigate retinal conditions due to the presence of various noises in the retinal image during the capture of t...

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Bibliographic Details
Published in:IET image processing 2019-12, Vol.13 (14), p.2778-2789
Main Authors: Ghosh, Swarup Kr, Biswas, Biswajit, Ghosh, Anupam
Format: Article
Language:English
Subjects:
biomedical optical imaging
blood vessels
convolution
deep learning
denoising effect
denoising images
diabetic retinopathy
diseases
eye
eye diseases
image denoising
image representation
image segmentation
learning (artificial intelligence)
medical image processing
neural nets
noise level
noisy fundus
novel stack deep convolutional autoencoder
patched base training
restoring features
retinal conditions
retinal fundus images
retinal image denoising
retinal vasculature
Special Section: Adversarial Learning in Image Processing
standard fundus databases
target image
visibility
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