Application of Deep Dictionary Learning and Predefined Filters for Classification of Retinal Optical Coherence Tomography Images
TL;DR
This paper introduces two methods combining deep learning with sparse representation for classifying retinal OCT images, aiming to improve abnormality detection while reducing computational demands and data needs.
Application of Deep Dictionary Learning and Predefined Filters for Classification of Retinal Optical Coherence Tomography Images
Fariba Shaker; Zahra Baharlouei; Gerlind Plonka; Hossein Rabbani
https://doi.org/10.1109/ACCESS.2024.3522122
Volume 13
In recent years, deep learning methods have excelled in Optical Coherence Tomography (OCT) image classification but demand high computational resources and extensive training data. We propose two effective methods for OCT image classification, combining the strength of deep learning with sparse representation of significant image features for improved detection of retinal abnormalities. The first ...