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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Detalhes bibliográficos

Principais autores:	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
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2021-12-01
coleção:	Sensors
Assuntos:	multiple sclerosis optical coherence tomography convolutional neural network generative adversarial network
Acesso em linha:	https://www.mdpi.com/1424-8220/22/1/167
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