A scoping review of transfer learning research on medical image analysis using ImageNet
Objective Employing transfer learning (TL) with convolutional neural networks (CNNs), well-
trained on non-medical ImageNet dataset, has shown promising results for medical image …
trained on non-medical ImageNet dataset, has shown promising results for medical image …
Detecting glaucoma with only OCT: Implications for the clinic, research, screening, and AI development
A method for detecting glaucoma based only on optical coherence tomography (OCT) is of
potential value for routine clinical decisions, for inclusion criteria for research studies and …
potential value for routine clinical decisions, for inclusion criteria for research studies and …
Automated glaucoma screening and diagnosis based on retinal fundus images using deep learning approaches: A comprehensive review
Glaucoma is a chronic eye disease that may lead to permanent vision loss if it is not
diagnosed and treated at an early stage. The disease originates from an irregular behavior …
diagnosed and treated at an early stage. The disease originates from an irregular behavior …
Assessment of a segmentation-free deep learning algorithm for diagnosing glaucoma from optical coherence tomography scans
Importance Conventional segmentation of the retinal nerve fiber layer (RNFL) is prone to
errors that may affect the accuracy of spectral-domain optical coherence tomography (SD …
errors that may affect the accuracy of spectral-domain optical coherence tomography (SD …
Automatic detection of diabetic eye disease through deep learning using fundus images: a survey
Diabetes Mellitus, or Diabetes, is a disease in which a person's body fails to respond to
insulin released by their pancreas, or it does not produce sufficient insulin. People suffering …
insulin released by their pancreas, or it does not produce sufficient insulin. People suffering …
A novel computer-aided diagnostic system for early detection of diabetic retinopathy using 3D-OCT higher-order spatial appearance model
Early diagnosis of diabetic retinopathy (DR) is of critical importance to suppress severe
damage to the retina and/or vision loss. In this study, an optical coherence tomography …
damage to the retina and/or vision loss. In this study, an optical coherence tomography …
Glaucoma diagnosis using multi-feature analysis and a deep learning technique
In this study, we aimed to facilitate the current diagnostic assessment of glaucoma by
analyzing multiple features and introducing a new cross-sectional optic nerve head (ONH) …
analyzing multiple features and introducing a new cross-sectional optic nerve head (ONH) …
Ophthalmic disease detection via deep learning with a novel mixture loss function
X Luo, J Li, M Chen, X Yang, X Li - IEEE Journal of Biomedical …, 2021 - ieeexplore.ieee.org
With the popularization of computer-aided diagnosis (CAD) technologies, more and more
deep learning methods are developed to facilitate the detection of ophthalmic diseases. In …
deep learning methods are developed to facilitate the detection of ophthalmic diseases. In …
An enhanced deep image model for glaucoma diagnosis using feature-based detection in retinal fundus
This paper proposes a deep image analysis–based model for glaucoma diagnosis that uses
several features to detect the formation of glaucoma in retinal fundus. These features are …
several features to detect the formation of glaucoma in retinal fundus. These features are …
Optical coherence tomography image classification using hybrid deep learning and ant colony optimization
Optical coherence tomography (OCT) is widely used to detect and classify retinal diseases.
However, OCT-image-based manual detection by ophthalmologists is prone to errors and …
However, OCT-image-based manual detection by ophthalmologists is prone to errors and …