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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Vydáno v:	Multiple sclerosis and related disorders Ročník 88; s. 105743
Hlavní autoři:	Aghababaei, Ali, Arian, Roya, Soltanipour, Asieh, Ashtari, Fereshteh, Rabbani, Hossein, Kafieh, Raheleh
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Netherlands Elsevier B.V 01.08.2024
Témata:	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
On-line přístup:	Získat plný text
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