Deep-learning based multiclass retinal fluid segmentation and detection in optical coherence tomography images using a fully convolutional neural network

D Lu, M Heisler, S Lee, GW Ding, E Navajas… - Medical image …, 2019 - Elsevier
As a non-invasive imaging modality, optical coherence tomography (OCT) can provide
micrometer-resolution 3D images of retinal structures. These images can help reveal …

RetiFluidNet: a self-adaptive and multi-attention deep convolutional network for retinal OCT fluid segmentation

R Rasti, A Biglari, M Rezapourian… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Optical coherence tomography (OCT) helps ophthalmologists assess macular edema,
accumulation of fluids, and lesions at microscopic resolution. Quantification of retinal fluids is …

Automatic fluid segmentation in retinal optical coherence tomography images using attention based deep learning

X Liu, S Wang, Y Zhang, D Liu, W Hu - Neurocomputing, 2021 - Elsevier
Optical coherence tomography (OCT) is one of the most commonly used ophthalmic
diagnostic techniques. Macular Edema (ME) is the swelling of the macular region in the eye …

RETOUCH: The retinal OCT fluid detection and segmentation benchmark and challenge

H Bogunović, F Venhuizen, S Klimscha… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
Retinal swelling due to the accumulation of fluid is associated with the most vision-
threatening retinal diseases. Optical coherence tomography (OCT) is the current standard of …

[HTML][HTML] Automated segmentation of retinal fluid volumes from structural and angiographic optical coherence tomography using deep learning

Y Guo, TT Hormel, H Xiong, J Wang… - … vision science & …, 2020 - iovs.arvojournals.org
Purpose: We proposed a deep convolutional neural network (CNN), named Retinal Fluid
Segmentation Network (ReF-Net), to segment retinal fluid in diabetic macular edema (DME) …

[HTML][HTML] Segmentation of retinal fluid based on deep learning: application of three-dimensional fully convolutional neural networks in optical coherence tomography …

MX Li, SQ Yu, W Zhang, H Zhou, X Xu… - International journal …, 2019 - ncbi.nlm.nih.gov
AIM To explore a segmentation algorithm based on deep learning to achieve accurate
diagnosis and treatment of patients with retinal fluid. METHODS A two-dimensional (2D) fully …

Multi-scale pathological fluid segmentation in OCT with a novel curvature loss in convolutional neural network

G Xing, L Chen, H Wang, J Zhang… - … on Medical Imaging, 2022 - ieeexplore.ieee.org
The segmentation of pathological fluid lesions in optical coherence tomography (OCT),
including intraretinal fluid, subretinal fluid, and pigment epithelial detachment, is of great …

RetFluidNet: retinal fluid segmentation for SD-OCT images using convolutional neural network

LB Sappa, IP Okuwobi, M Li, Y Zhang, S Xie… - Journal of Digital …, 2021 - Springer
Age-related macular degeneration (AMD) is one of the leading causes of irreversible
blindness and is characterized by fluid-related accumulations such as intra-retinal fluid …

Deep-learning based, automated segmentation of macular edema in optical coherence tomography

CS Lee, AJ Tyring, NP Deruyter, Y Wu… - Biomedical optics …, 2017 - opg.optica.org
Evaluation of clinical images is essential for diagnosis in many specialties. Therefore the
development of computer vision algorithms to help analyze biomedical images will be …

Retinal fluid segmentation in OCT images using adversarial loss based convolutional neural networks

R Tennakoon, AK Gostar… - 2018 IEEE 15th …, 2018 - ieeexplore.ieee.org
This paper proposes a novel method in order to obtain voxel-level segmentation for three
fluid lesion types (IR-F/SRF/PED) in OCT images provided by the ReTOUCH challenge [1] …