Joint segmentation and quantification of chorioretinal biomarkers in optical coherence tomography scans: A deep learning approach

B Hassan, S Qin, T Hassan, R Ahmed… - IEEE Transactions on …, 2021‏ - ieeexplore.ieee.org
In ophthalmology, chorioretinal biomarkers (CRBMs) play a significant role in detecting,
quantifying, and ameliorating the treatment of chronic eye conditions. Optical coherence …

Glaucoma detection from raw SD-OCT volumes: a novel approach focused on spatial dependencies

G García, A Colomer, V Naranjo - Computer methods and programs in …, 2021‏ - Elsevier
Background and objective: Glaucoma is the leading cause of blindness worldwide. Many
studies based on fundus image and optical coherence tomography (OCT) imaging have …

[HTML][HTML] Does real-time artificial intelligence-based visual pathology enhancement of three-dimensional optical coherence tomography scans optimise treatment …

FG Holz, R Abreu-Gonzalez, F Bandello… - British Journal of …, 2023‏ - bjo.bmj.com
Background/rationale Artificial intelligence (AI)-based clinical decision support tools, being
developed across multiple fields in medicine, need to be evaluated for their impact on the …

[HTML][HTML] VLFATRollout: Fully transformer-based classifier for retinal OCT volumes

M Oghbaie, T Araújo, U Schmidt-Erfurth… - … Medical Imaging and …, 2024‏ - Elsevier
Abstract Background and Objective: Despite the promising capabilities of 3D transformer
architectures in video analysis, their application to high-resolution 3D medical volumes …

Spatial-aware transformer-GRU framework for enhanced glaucoma diagnosis from 3D OCT imaging

M Ashtari-Majlan, MM Dehshibi, D Masip - arxiv preprint arxiv:2403.05702, 2024‏ - arxiv.org
Glaucoma, a leading cause of irreversible blindness, necessitates early detection for
accurate and timely intervention to prevent irreversible vision loss. In this study, we present a …

A framework for robust glaucoma detection: A confidence-aware deep uncertainty quantification approach with a comprehensive assessment for enhanced clinical …

J Zarean, AR Tajally, R Tavakkoli-Moghaddam… - … Applications of Artificial …, 2025‏ - Elsevier
Glaucoma poses a significant threat to public health worldwide, as it can result in irreversible
vision loss. Timely identification is vital for halting the progression of visual field …

Predicting OCT biological marker localization from weak annotations

JG Tejero, PM Neila, T Kurmann, M Gallardo… - Scientific Reports, 2023‏ - nature.com
Recent developments in deep learning have shown success in accurately predicting the
location of biological markers in Optical Coherence Tomography (OCT) volumes of patients …

Pretrained deep 2.5 D models for efficient predictive modeling from retinal OCT: a PINNACLE study report

T Emre, M Oghbaie, A Chakravarty, A Rivail… - … on Ophthalmic Medical …, 2023‏ - Springer
In the field of medical imaging, 3D deep learning models play a crucial role in building
powerful predictive models of disease progression. However, the size of these models …

An Intestinal Tumors Detection Model Based on Feature Distillation With Self-Correction Mechanism and PathGAN

L Zhu, J Liu, D Zheng, Z Cao, F Miao, C Li, J He… - IEEE …, 2024‏ - ieeexplore.ieee.org
Small intestine tumors are gastrointestinal tumors with unclear clinical manifestations, and
the current diagnosis relies on expert analysis of abdominal Computed Tomography (CT) …

Deep learning for ophthalmology using optical coherence tomography

HA Leopold, A Singh, S Sengupta… - State of the Art in Neural …, 2021‏ - Elsevier
The majority of recent deep learning research has been the reapplication of established
image-processing techniques to retinal images. Another prominent and substantially richer …