Preface - 11th International Workshop on Ophthalmic Medical Image Analysis, OMIA-XI 2024 was held in conjunction with the 27th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2024

• Book Chapters
• DOI reference:

A novel predictive model utilizing retinal microstructural features for estimating survival outcome in patients with glioblastoma

• Journals
• DOI reference: 10.1016/j.clineuro.2025.108790

Normative Variability in Retinal Nerve Fiber Layer Thickness: Does It Matter Where the Peaks Are?

• Journals
• DOI reference: 10.1167/tvst.14.5.13

A Hybrid Deep Learning-Based Approach for Visual Field Test Forecasting

• Journals
• DOI reference: 10.1016/j.xops.2025.100803

DIRECTIONAL OPTICAL COHERENCE TOMOGRAPHY IMAGING OF MACULAR PATHOLOGY

• Journals
• DOI reference: 10.1097/IAE.0000000000004105

Retinal Microstructural Changes Reflecting Treatment-Associated Cognitive Dysfunction in Patients with Lower-Grade Gliomas

• Journals
• DOI reference: 10.1016/j.xops.2024.100577

Predicting Pseudomonas aeruginosa drug resistance using artificial intelligence and clinical MALDI-TOF mass spectra

• Journals
• DOI reference: 10.1128/msystems.00789-24

Navigating the Terrain of Large Language Models in Higher Education- A systematic literature review

• Conference Proceedings
• DOI reference:

Navigating the Terrain of Large Language Models in Higher Education- A systematic literature review

• Conference Proceedings
• DOI reference:

A Multi-Modal AI-Driven Cohort Selection Tool to Predict Suboptimal Non-Responders to Aflibercept Loading-Phase for Neovascular Age-Related Macular Degeneration: PRECISE Study Report 1

• Journals
• DOI reference: 10.3390/jcm12083013

Mixed multiscale BM4D for three-dimensional optical coherence tomography denoising

• Journals
• DOI reference: 10.1016/j.compbiomed.2023.106658

A Case for the Use of Artificial Intelligence in Glaucoma Assessment

• Journals
• DOI reference: 10.1016/j.ogla.2021.12.003

Directional reflectivity of the ellipsoid zone in dry age-related macular degeneration

• Journals
• DOI reference: 10.3928/23258160-20210302-05

Estimating Global Visual Field Indices in Glaucoma by Combining Macula and Optic Disc OCT Scans Using 3-Dimensional Convolutional Neural Networks

• Journals
• DOI reference: 10.1016/j.ogla.2020.07.002

Attention-Guided 3D-CNN Framework for Glaucoma Detection and Structural-Functional Association Using Volumetric Images

• Journals
• DOI reference: 10.1109/JBHI.2020.3001019

Forecasting Retinal Nerve Fiber Layer Thickness from Multimodal Temporal Data Incorporating OCT Volumes

• Journals
• DOI reference: 10.1016/j.ogla.2019.11.001

Uncertainty guided semi-supervised segmentation of retinal layers in OCT images

• Conference Proceedings
• DOI reference: 10.1007/978-3-030-32239-7_32

3D-CNN for Glaucoma Detection Using Optical Coherence Tomography

• Conference Proceedings
• DOI reference: 10.1007/978-3-030-32956-3_7

Layer boundary evolution method for macular OCT layer segmentation

• Journals
• DOI reference: 10.1364/BOE.10.001064

A new promising way for tackling the 'Pharma Dilemma': Artificial intelligence for clinical trials

• Journals
• DOI reference: 10.1042/bio04105010

Artificial Intelligence for Clinical Trial Design

• Journals
• DOI reference: 10.1016/j.tips.2019.05.005

A feature agnostic approach for glaucoma detection in OCT volumes

• Journals
• DOI reference: 10.1371/journal.pone.0219126

Automated summarisation of SDOCT volumes using deep learning: Transfer learning vs de novo trained networks

• Journals
• DOI reference: 10.1371/journal.pone.0203726

Joint Segmentation and Uncertainty Visualization of Retinal Layers in Optical Coherence Tomography Images Using Bayesian Deep Learning

• Conference Proceedings
• DOI reference: 10.1007/978-3-030-00949-6_26

Deformable medical image registration using generative adversarial networks

• Conference Proceedings
• DOI reference: 10.1109/ISBI.2018.8363845

Retinal optical coherence tomography image enhancement via deep learning

• Journals
• DOI reference: 10.1364/BOE.9.006205

The henle fiber layer in albinism: Comparison to normal and relationship to outer nuclear layer thickness and foveal cone density

• Journals
• DOI reference: 10.1167/iovs.18-24145

Analysis of Agreement of Retinal-Layer Thickness Measures Derived from the Segmentation of Horizontal and Vertical Spectralis OCT Macular Scans

• Journals
• DOI reference: 10.1080/02713683.2017.1406526

Longitudinal Analysis of Mouse SDOCT Volumes

• Conference Proceedings
• DOI reference: 10.1117/12.2257432

Collaborative SDOCT segmentation and analysis software

• Conference Proceedings
• DOI reference:

Automated segmentation of mouse OCT volumes (ASiMOV): Validation & clinical study of a light damage model

• Journals
• DOI reference: 10.1371/journal.pone.0181059

3D graph-based automated segmentation of corneal layers in anterior-segment optical coherence tomography images of mice

• Conference Proceedings
• DOI reference: 10.1117/12.2043523

Incorporation of learned shape priors into a graph-theoretic approach with application to the 3D segmentation of intraretinal surfaces in SD-OCT volumes of mice

• Conference Proceedings
• DOI reference: 10.1117/12.2043203

Automated 3D segmentation of multiple surfaces with a shared hole: Segmentation of the neural canal opening in SD-OCT volumes

• Conference Proceedings
• DOI reference: 10.1007/978-3-319-10404-1_92

Voxel based morphometry in optical coherence tomography: Validation & core findings

• Conference Proceedings
• DOI reference: 10.1117/12.2216096

Automated 3-D segmentation of intraretinal layers from optic nerve head optical coherence tomography images

• Conference Proceedings
• DOI reference: 10.1117/12.843928

Incorporation of Texture-based Features in Optimal Graph-Theoretic Approach with Application to the 3-D Segmentation of Intraretinal Surfaces in SD-OCT Volumes

• Conference Proceedings
• DOI reference: 10.1117/12.911491

Simultaneous Segmentation of Retinal Surfaces and Microcystic Macular Edema in SDOCT Volumes

• Conference Proceedings
• DOI reference: 10.1117/12.2214676

Novel method using 3-dimensional segmentation in spectral domain-optical coherence tomography imaging in the chick reveals defocus-induced regional and time-sensitive asymmetries in the choroidal thickness

• Journals
• DOI reference: 10.1017/S0952523816000067

Directional Optical Coherence Tomography Provides Accurate Outer Nuclear Layer and Henle Fiber Layer Measurements

• Journals
• DOI reference: 10.1097/IAE.0000000000000527

A combined machine-learning and graph-based framework for the segmentation of retinal surfaces in SD-OCT volumes

• Journals
• DOI reference: 10.1364/BOE.4.002712

Automated 3-D method for the correction of axial artifacts in spectral-domain optical coherence tomography images

• Journals
• DOI reference: 10.1364/BOE.2.002403