Early Diagnosis of Multiple Sclerosis Using Swept-Source Optical Coherence Tomography and Convolutional Neural Networks Trained with Data Augmentation

Early Diagnosis of Multiple Sclerosis Using Swept-Source Optical Coherence Tomography and Convolutional Neural Networks Trained with Data Augmentation

Background: The aim of this paper is to implement a system to facilitate the diagnosis of multiple sclerosis (MS) in its initial stages. It does so using a convolutional neural network (CNN) to classify images captured with swept-source optical coherence tomography (SS-OCT). Methods: SS-OCT images f...

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Bibliographic Details
Main Authors: Almudena López-Dorado, Miguel Ortiz, María Satue, María J. Rodrigo, Rafael Barea, Eva M. Sánchez-Morla, Carlo Cavaliere, José M. Rodríguez-Ascariz, Elvira Orduna-Hospital, Luciano Boquete, Elena Garcia-Martin
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Sensors
Subjects:
multiple sclerosis
optical coherence tomography
convolutional neural network
generative adversarial network
Online Access:https://www.mdpi.com/1424-8220/22/1/167

Internet

https://www.mdpi.com/1424-8220/22/1/167

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