A Device-Independent, Shape Preserving Retinal Optical Coherence Tomography Image Alignment Method Applying TV-Unet for RPE Layer Detection

Author:

Saeedizadeh Narges1ORCID,Tajmirriahi Mahnoosh1ORCID,Haghani Alireza1ORCID,Amini Zahra1ORCID,Pour Elias Khalili2ORCID,Riazi-Esfahani Hamid2ORCID,Fadakar Kaveh2ORCID,Kafieh Rahele1ORCID,Rabbani Hossein1ORCID

Affiliation:

1. Medical Image and Signal Processing Research Center, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

2. Retina Ward, Farabi Eye Hospital, Tehran University of Medical Sciences, Tehran, Iran

Funder

Leading House South Asia and Iran, Zurich University of Applied Sciences, Switzerland, through the Research Seed Money Grant

National Institute for Medical Research Development

Vice-Chancellery for Research and Technology, Isfahan University of Medical Sciences

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Reference34 articles.

1. Unsupervised image segmentation using convolutional autoencoder with total variation regularization as preprocessing

2. MR image segmentation and bias field estimation based on coherent local intensity clustering with total variation regularization

3. Nonlinear total variation based noise removal algorithms

4. U-Net: Convolutional networks for biomedical image segmentation;ronneberger;Proc Med Image Comput Comput -Assist Intervent,2015

5. The improvement of extraction retinal pigment epithelium (RPE) layer in optical coherence tomography (OCT) images by using piecewise dynamic programming method in patients with persistent epithelial defect (PED);haghani;Journal of Isfahan Medical School,2021

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