Embedded residual recurrent network and graph search for the segmentation of retinal layer boundaries in optical coherence tomography
For the study of various retinal diseases, an accurate quantitative analysis of the retinal layer
is essential for assessing the severity of the disease and diagnosing the progression of the …
is essential for assessing the severity of the disease and diagnosing the progression of the …
[HTML][HTML] A novel convolutional neural network for identification of retinal layers using sliced optical coherence tomography images
Retinal imaging is crucial for observing the retina and accurately diagnosing pathological
problems. Optical Coherence Tomography (OCT) has been a transformative breakthrough …
problems. Optical Coherence Tomography (OCT) has been a transformative breakthrough …
Benchmarking automated detection of the retinal external limiting membrane in a 3D spectral domain optical coherence tomography image dataset of full thickness …
In this article, we present a new benchmark for the segmentation of the retinal external
limiting membrane (ELM) using an image dataset of spectral domain optical coherence …
limiting membrane (ELM) using an image dataset of spectral domain optical coherence …
SEADNet: Deep learning driven segmentation and extraction of macular fluids in 3D retinal OCT scans
In ophthalmology, symptomatic exudate-associated derangement (SEAD) lesions play an
important role in the timely intervention and treatment of maculopathy. Optical coherence …
important role in the timely intervention and treatment of maculopathy. Optical coherence …
MPG-Net: multi-prediction guided network for segmentation of retinal layers in OCT images
Optical coherence tomography (OCT) is a commonly-used method of extracting high
resolution retinal information. Moreover there is an increasing demand for the automated …
resolution retinal information. Moreover there is an increasing demand for the automated …
MACULA OCT Disease Images Classification using Deep Learning Techniques
R Vasanthi, SSS Sowmya, SS Madhura… - 2024 5th International …, 2024 - ieeexplore.ieee.org
This study explores the transformative impact of deep learning techniques, particularly in
ophthalmology, on medical image analysis, with a specific focus on the automated …
ophthalmology, on medical image analysis, with a specific focus on the automated …
Generative adversarial learning for semi-supervised retinal layer segmentation in OCT images
It is often challenging to obtain large number of labeled data for retinal layer segmentation in
optical coherence tomography scans due to the need for expert ophthalmologists. On the …
optical coherence tomography scans due to the need for expert ophthalmologists. On the …