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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Veröffentlicht in:	Multiple sclerosis and related disorders Jg. 88; S. 105743
Hauptverfasser:	Aghababaei, Ali, Arian, Roya, Soltanipour, Asieh, Ashtari, Fereshteh, Rabbani, Hossein, Kafieh, Raheleh
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Netherlands Elsevier B.V 01.08.2024
Schlagworte:	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-Zugang:	Volltext
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