Discrimination of multiple sclerosis using scanning laser ophthalmoscopy images with autoencoder-based feature extraction

Optical coherence tomography (OCT) investigations have revealed that the thickness of inner retinal layers becomes decreased in multiple sclerosis (MS) patients, compared to healthy control (HC) individuals. To date, a number of studies have applied machine learning to OCT thickness measurements, ai...

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Bibliographic Details
Published in:	Multiple sclerosis and related disorders Vol. 88; p. 105743
Main Authors:	Aghababaei, Ali, Arian, Roya, Soltanipour, Asieh, Ashtari, Fereshteh, Rabbani, Hossein, Kafieh, Raheleh
Format:	Journal Article
Language:	English
Published:	Netherlands Elsevier B.V 01.08.2024
Subjects:	Adult Deep Learning Feature Extraction Female Humans Machine Learning Male Middle Aged Multiple Sclerosis Multiple Sclerosis - diagnostic imaging Neural Networks, Computer Neurology Ophthalmoscopy - methods Optical Coherence Tomography Scanning Laser Ophthalmoscopy Sensitivity and Specificity Tomography, Optical Coherence - methods Multiple Sclerosis Feature Extraction Optical Coherence Tomography Scanning Laser Ophthalmoscopy Machine Learning Deep Learning
ISSN:	2211-0348, 2211-0356, 2211-0356
Online Access:	Get full text
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