Reconstruction and Quantification of 3D Iris Surface for Angle-Closure Glaucoma Detection in Anterior Segment OCT (2020-06-09T00:00:00.000000Z)

TL;DR

Experimental results demonstrate that the proposed novel framework for reconstruction and quantification of 3D iris surface from AS-OCT imagery is highly effective in iris segmentation and surface reconstruction and it is shown that 3D-based representation achieves better performance in angle-closure glaucoma detection than does 2D- based feature.

Abstract

Precise characterization and analysis of iris shape from Anterior Segment OCT (AS-OCT) are of great importance in facilitating diagnosis of angle-closure-related diseases. Existing methods focus solely on analyzing structural properties identified from the 2D slice, while accurate characterization of morphological changes of iris shape in 3D AS-OCT may be able to reveal in addition the risk of disease progression. In this paper, we propose a novel framework for reconstruction and quantification of 3D iris surface from AS-OCT imagery. We consider it to be the first work to detect angle-closure glaucoma by means of 3D representation. An iris segmentation network with wavelet refinement block (WRB) is first proposed to generate the initial shape of the iris from single AS-OCT slice. The 3D iris surface is then reconstructed using a guided optimization method with Poisson-disk sampling. Finally, a set of surface-based features are extracted, which are used in detecting of angle-closure glaucoma. Experimental results demonstrate that our method is highly effective in iris segmentation and surface reconstruction. Moreover, we show that 3D-based representation achieves better performance in angle-closure glaucoma detection than does 2D-based feature.

Authors

Yan Hu

4 papers

Jiang Liu

6 papers

H. Fu

27 papers

Reconstruction and Quantification of 3D Iris Surface for Angle-Closure Glaucoma Detection in Anterior Segment OCT

TL;DR

Abstract

Authors

References27 items

Automated Tortuosity Analysis of Nerve Fibers in Corneal Confocal Microscopy

Retinal Vascular Network Topology Reconstruction and Artery/Vein Classification via Dominant Set Clustering

Deep Learning Classifiers for Automated Detection of Gonioscopic Angle Closure Based on Anterior Segment OCT Images.

Automated Iris Segmentation from Anterior Segment OCT Images with Occludable Angles via Local Phase Tensor

A Deep Learning System for Automated Angle-Closure Detection in Anterior Segment Optical Coherence Tomography Images.

CE-Net: Context Encoder Network for 2D Medical Image Segmentation

Angle-Closure Detection in Anterior Segment OCT Based on Multilevel Deep Network

Uniqueness-Driven Saliency Analysis for Automated Lesion Detection with Applications to Retinal Diseases

Multi-context Deep Network for Angle-Closure Glaucoma Screening in Anterior Segment OCT

Anterior segment optical coherence tomography

Anterior Segment Imaging for Angle Closure.

Automatic 2-D/3-D Vessel Enhancement in Multiple Modality Images Using a Weighted Symmetry Filter

Segmentation and Quantification for Angle-Closure Glaucoma Assessment in Anterior Segment OCT

Evaluation of circumferential angle closure using iridotrabecular contact index after laser iridotomy by swept‐source optical coherence tomography

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

Region-based saliency estimation for 3D shape analysis and understanding

Deep Residual Learning for Image Recognition

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

Comparison of Ocular Biometry Between Eyes With Chronic Primary Angle-Closure Glaucoma and their Fellow Eyes With Primary Angle-Closure or Primary Angle-Closure Suspect

Fully convolutional networks for semantic segmentation

Very Deep Convolutional Networks for Large-Scale Image Recognition

Anterior Chamber Angle Shape Analysis and Classification of Glaucoma in SS-OCT Images

ImageNet classification with deep convolutional neural networks

Anterior chamber angle classification using multiscale histograms of oriented gradients for glaucoma subtype identification

Quantitative iris parameters and association with narrow angles.

Ieee Transactions on Visualization and Computer Graphics 1 Efficient and Flexible Sampling with Blue Noise Properties of Triangular Meshes

Field of Study

Venue Information

Name

Type

URL

Alternate Names