Radiomics-Based Assessment of OCT Angiography Images for Diabetic Retinopathy Diagnosis

Radiomics-Based Assessment of OCT Angiography Images for Diabetic Retinopathy Diagnosis

Purpose: To evaluate the diagnostic accuracy of machine learning (ML) techniques applied to radiomic features extracted from OCT and OCT angiography (OCTA) images for diabetes mellitus (DM), diabetic retinopathy (DR), and referable DR (R-DR) diagnosis. Design: Cross-sectional analysis of a retinal i...

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Main Authors: Laura Carrera-Escalé, MSc, Anass Benali, MSc, Ann-Christin Rathert, MSc, Ruben Martín-Pinardel, MSc, Carolina Bernal-Morales, MD, PhD, Anibal Alé-Chilet, MD, Marina Barraso, MD, PhD, Sara Marín-Martinez, MD, Silvia Feu-Basilio, MD, Josep Rosinés-Fonoll, MD, Teresa Hernandez, OD, Irene Vilá, OD, Rafael Castro-Dominguez, OD, Cristian Oliva, OD, Irene Vinagre, MD, PhD, Emilio Ortega, MD, PhD, Marga Gimenez, MD, PhD, Alfredo Vellido, PhD, Enrique Romero, PhD, Javier Zarranz-Ventura, MD, PhD
Format: Article
Language:English
Published: Elsevier 2023-06-01
Series:Ophthalmology Science
Subjects:
Artificial intelligence
Diabetic retinopathy
Machine learning
OCT angiography
Radiomics
Online Access:http://www.sciencedirect.com/science/article/pii/S2666914522001488

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http://www.sciencedirect.com/science/article/pii/S2666914522001488

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