Automated assessment of the smoothness of retinal layers in optical coherence tomography images using a machine learning algorithm

Automated assessment of the smoothness of retinal layers in optical coherence tomography images using a machine learning algorithm

Abstract Quantifying the smoothness of different layers of the retina can potentially be an important and practical biomarker in various pathologic conditions like diabetic retinopathy. The purpose of this study is to develop an automated machine learning algorithm which uses support vector regressi...

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Bibliographic Details
Main Authors: Jamshid Saeidian, Tahereh Mahmoudi, Hamid Riazi-Esfahani, Zahra Montazeriani, Alireza Khodabande, Mohammad Zarei, Nazanin Ebrahimiadib, Behzad Jafari, Alireza Afzal Aghaei, Hossein Azimi, Elias Khalili Pour
Format: Article
Language:English
Published: BMC 2023-02-01
Series:BMC Medical Imaging
Subjects:
Automated segmentation
Support vector regression
Inner plexiform layer
Outer plexiform Layer
Bland-Altman plot
Biomarker
Online Access:https://doi.org/10.1186/s12880-023-00976-w

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