Classification of diabetes-related retinal diseases using a deep learning approach in optical coherence tomography

Oscar Perdómo; Hernán Andrés Ríos; Francisco J. Rodríguez; Sebastian Otálora; Fabrice Mériaudeau; Henning Müller; Fabio A. González

doi:10.1016/j.cmpb.2019.06.016

JOURNAL ARTICLE

Classification of diabetes-related retinal diseases using a deep learning approach in optical coherence tomography

Oscar Perdómo Hernán Andrés Ríos Francisco J. Rodríguez Sebastian Otálora Fabrice Mériaudeau Henning Müller Fabio A. González

Year: 2019 Journal: Computer Methods and Programs in Biomedicine Vol: 178 Pages: 181-189 Publisher: Elsevier BV

DOI: 10.1016/j.cmpb.2019.06.016

Get Full-Text PDF Get Analytical Report

Keywords:

Optical coherence tomography Deep learning Artificial intelligence Convolutional neural network Computer science Diabetic retinopathy Machine learning Medical imaging Pattern recognition (psychology) Medicine Diabetes mellitus Ophthalmology

Metrics

Cited By

7.72

FWCI (Field Weighted Citation Impact)

Refs

0.97

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Retinal Imaging and Analysis

Health Sciences → Medicine → Radiology, Nuclear Medicine and Imaging

Artificial Intelligence in Healthcare

Health Sciences → Health Professions → Health Information Management

Digital Imaging for Blood Diseases

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Classification of diabetes-related retinal diseases using a deep learning approach in optical coherence tomography

Metrics

Citation History

Topics

Related Documents

Retinal Optical Coherence Tomography Classification Using Deep Learning

Optimizing deep learning based retinal diseases classification on optical coherence tomography scans

Optical coherence tomography retinal classification using deep neural network

Deep learning with adaptive convolutions for classification of retinal diseases via optical coherence tomography

Retinal diseases classification based on hybrid ensemble deep learning and optical coherence tomography images