A holistic overview of deep learning approach in medical imaging
Medical images are a rich source of invaluable necessary information used by clinicians.
Recent technologies have introduced many advancements for exploiting the most of this …
Recent technologies have introduced many advancements for exploiting the most of this …
Computer aided diagnosis of diabetic macular edema in retinal fundus and OCT images: A review
KC Pavithra, P Kumar, M Geetha… - Biocybernetics and …, 2023 - Elsevier
Abstract Diabetic Macular Edema (DME) is a potentially blinding consequence of Diabetic
Retinopathy (DR) as well as the leading cause of vision loss in diabetics. DME is …
Retinopathy (DR) as well as the leading cause of vision loss in diabetics. DME is …
Octnet: A lightweight cnn for retinal disease classification from optical coherence tomography images
Abstract Background and Objective Retinal diseases are becoming a major health problem
in recent years. Their early detection and ensuing treatment are essential to prevent visual …
in recent years. Their early detection and ensuing treatment are essential to prevent visual …
AOCT-NET: a convolutional network automated classification of multiclass retinal diseases using spectral-domain optical coherence tomography images
AM Alqudah - Medical & biological engineering & computing, 2020 - Springer
Since introducing optical coherence tomography (OCT) technology for 2D eye imaging, it
has become one of the most important and widely used imaging modalities for the …
has become one of the most important and widely used imaging modalities for the …
[HTML][HTML] DeepOCT: An explainable deep learning architecture to analyze macular edema on OCT images
G Altan - Engineering Science and Technology, an International …, 2022 - Elsevier
Macular edema (ME) is one of the most common retinal diseases that occur as a result of the
detachment of the retinal layers on the macula. This study provides computer-aided …
detachment of the retinal layers on the macula. This study provides computer-aided …
Conv-ViT: a convolution and vision transformer-based hybrid feature extraction method for retinal disease detection
The current advancement towards retinal disease detection mainly focused on distinct
feature extraction using either a convolutional neural network (CNN) or a transformer-based …
feature extraction using either a convolutional neural network (CNN) or a transformer-based …
RetiFluidNet: a self-adaptive and multi-attention deep convolutional network for retinal OCT fluid segmentation
Optical coherence tomography (OCT) helps ophthalmologists assess macular edema,
accumulation of fluids, and lesions at microscopic resolution. Quantification of retinal fluids is …
accumulation of fluids, and lesions at microscopic resolution. Quantification of retinal fluids is …
A deep learning approach to denoise optical coherence tomography images of the optic nerve head
Optical coherence tomography (OCT) has become an established clinical routine for the in
vivo imaging of the optic nerve head (ONH) tissues, that is crucial in the diagnosis and …
vivo imaging of the optic nerve head (ONH) tissues, that is crucial in the diagnosis and …
Convolution neural networks for optical coherence tomography (OCT) image classification
K Karthik, M Mahadevappa - Biomedical Signal Processing and Control, 2023 - Elsevier
Optical coherence tomography (OCT) is an imaging modality used to obtain a cross-
sectional image of the retina for retinal disease diagnosis. Modern diagnosis systems use …
sectional image of the retina for retinal disease diagnosis. Modern diagnosis systems use …
Multilevel deep feature generation framework for automated detection of retinal abnormalities using OCT images
Optical coherence tomography (OCT) images coupled with many learning techniques have
been developed to diagnose retinal disorders. This work aims to develop a novel framework …
been developed to diagnose retinal disorders. This work aims to develop a novel framework …