activity
20172023
most citedDRUNET: A Dilated-Residual U-Net Deep Learning Network to Digitally Stain Optic Nerve Head Tissues in Optical Coherence Tomography Images

5 citations · 21 across the 15 of their papers we have counts for

collaborators
Showing eess.IVShow all

10 papers · 1 filter

eess.IV2022

AI-based Clinical Assessment of Optic Nerve Head Robustness Superseding Biomechanical Testing

Fabian A. Braeu, Thanadet Chuangsuwanich, Tin A. Tun +4

: To use artificial intelligence (AI) to: (1) exploit biomechanical knowledge of the optic nerve head (ONH) from a relatively large population; (2) assess ONH rob…

eess.IV2022★ 2 cited

Geometric Deep Learning to Identify the Critical 3D Structural Features of the Optic Nerve Head for Glaucoma Diagnosis

Fabian A. Braeu, Alexandre H. Thiéry, Tin A. Tun +4

Purpose: The optic nerve head (ONH) undergoes complex and deep 3D morphological changes during the development and progression of glaucoma. Optical coherence tomography (OCT) is th…

eess.IV2022★ 3 cited

Medical Application of Geometric Deep Learning for the Diagnosis of Glaucoma

Alexandre H. Thiery, Fabian Braeu, Tin A. Tun +2

Purpose: (1) To assess the performance of geometric deep learning (PointNet) in diagnosing glaucoma from a single optical coherence tomography (OCT) 3D scan of the optic nerve head…

eess.IV2021★ 2 cited

3D Structural Analysis of the Optic Nerve Head to Robustly Discriminate Between Papilledema and Optic Disc Drusen

Michaël J. A. Girard, Satish K. Panda, Tin Aung Tun +7

Purpose: (1) To develop a deep learning algorithm to identify major tissue structures of the optic nerve head (ONH) in 3D optical coherence tomography (OCT) scans; (2) to exploit s…

eess.IV2021

The Three-Dimensional Structural Configuration of the Central Retinal Vessel Trunk and Branches as a Glaucoma Biomarker

Satish K. Panda, Haris Cheong, Tin A. Tun +10

Purpose: To assess whether the three-dimensional (3D) structural configuration of the central retinal vessel trunk and its branches (CRVT&B) could be used as a diagnostic marker fo…

eess.IV2020

Describing the Structural Phenotype of the Glaucomatous Optic Nerve Head Using Artificial Intelligence

Satish K. Panda, Haris Cheong, Tin A. Tun +8

The optic nerve head (ONH) typically experiences complex neural- and connective-tissue structural changes with the development and progression of glaucoma, and monitoring these cha…

eess.IV2020

OCT-GAN: Single Step Shadow and Noise Removal from Optical Coherence Tomography Images of the Human Optic Nerve Head

Haris Cheong, Sripad Krishna Devalla, Thanadet Chuangsuwanich +8

Speckle noise and retinal shadows within OCT B-scans occlude important edges, fine textures and deep tissues, preventing accurate and robust diagnosis by algorithms and clinicians.…

eess.IV2020★ 4 cited

Towards Label-Free 3D Segmentation of Optical Coherence Tomography Images of the Optic Nerve Head Using Deep Learning

Sripad Krishna Devalla, Tan Hung Pham, Satish Kumar Panda +16

Since the introduction of optical coherence tomography (OCT), it has been possible to study the complex 3D morphological changes of the optic nerve head (ONH) tissues that occur al…

eess.IV2019

DeshadowGAN: A Deep Learning Approach to Remove Shadows from Optical Coherence Tomography Images

Haris Cheong, Sripad Krishna Devalla, Tan Hung Pham +9

Purpose: To remove retinal shadows from optical coherence tomography (OCT) images of the optic nerve head(ONH). Methods:2328 OCT images acquired through the center of the ONH using…

eess.IV2019

Deep Learning Algorithms to Isolate and Quantify the Structures of the Anterior Segment in Optical Coherence Tomography Images

Tan Hung Pham, Sripad Krishna Devalla, Aloysius Ang +6

Accurate isolation and quantification of intraocular dimensions in the anterior segment (AS) of the eye using optical coherence tomography (OCT) images is important in the diagnosi…