1. Articles from Pheng-Ann Heng

    1-3 of 3
    1. Towards multi-center glaucoma OCT image screening with semi-supervised joint structure and function multi-task learning

      Towards multi-center glaucoma OCT image screening with semi-supervised joint structure and function multi-task learning

      Glaucoma is the leading cause of irreversible blindness in the world. Structure and function assessments play an important role in diagnosing glaucoma. Nowadays, Optical Coherence Tomography (OCT) imaging gains increasing popularity in measuring the structural change of eyes. However, few automated methods have been developed based on OCT images to screen glaucoma. In this paper, we are the first to unify the structure analysis and function regression to distinguish glaucoma patients from normal controls effectively. Specifically, our method works in two steps: a semi-supervised learning strategy with smoothness assumption is first applied for the surrogate assignment of missing function regression ...

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    2. Detection of glaucomatous optic neuropathy with spectral-domain optical coherence tomography: a retrospective training and validation deep-learning analysis

      Detection of glaucomatous optic neuropathy with spectral-domain optical coherence tomography: a retrospective training and validation deep-learning analysis

      Background Spectral-domain optical coherence tomography (SDOCT) can be used to detect glaucomatous optic neuropathy, but human expertise in interpretation of SDOCT is limited. We aimed to develop and validate a three-dimensional (3D) deep-learning system using SDOCT volumes to detect glaucomatous optic neuropathy. Methods We retrospectively collected a dataset including 4877 SDOCT volumes of optic disc cube for training (60%), testing (20%), and primary validation (20%) from electronic medical and research records at the Chinese University of Hong Kong Eye Centre (Hong Kong, China) and the Hong Kong Eye Hospital (Hong Kong, China). Residual network was used to build the 3D ...

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    3. Unifying Structure Analysis and Surrogate-driven Function Regression for Glaucoma OCT Image Screening

      Unifying Structure Analysis and Surrogate-driven Function Regression for Glaucoma OCT Image Screening

      Optical Coherence Tomography (OCT) imaging plays an important role in glaucoma diagnosis in clinical practice. Early detection and timely treatment can prevent glaucoma patients from permanent vision loss. However, only a dearth of automated methods has been developed based on OCT images for glaucoma study. In this paper, we present a novel framework to effectively classify glaucoma OCT images from normal ones. A semi-supervised learning strategy with smoothness assumption is applied for surrogate assignment of missing function regression labels. Besides, the proposed multi-task learning network is capable of exploring the structure and function relationship from the OCT image and visual ...

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    1-3 of 3
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    1. (3 articles) The Chinese University of Hong Kong
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    Unifying Structure Analysis and Surrogate-driven Function Regression for Glaucoma OCT Image Screening Detection of glaucomatous optic neuropathy with spectral-domain optical coherence tomography: a retrospective training and validation deep-learning analysis Towards multi-center glaucoma OCT image screening with semi-supervised joint structure and function multi-task learning High space-bandwidth in quantitative phase imaging using partially spatially coherent optical coherence microscopy and deep neural network Optical coherence tomography assessment of macrophages accumulation in non-ST-segment elevation acute coronary syndromes Early disability in ambulatory patients with multiple sclerosis: optical coherence tomography versus visual evoked potentials, a comparative study Dueling Deep Q-Network for Unsupervised Inter-frame Eye Movement Correction in Optical Coherence Tomography Volumes Atlas of Optical Coherence Tomography for Glaucoma (Textbook) In-vivo analysis of iron-gold composite nanoparticles as potential exogenous contrast agents for Magnetomotive Optical Coherence Tomography (MMOCT) Automatic Classification of Volumetric Optical Coherence Tomography Images via Recurrent Neural Network Noise-Powered Disentangled Representation for Unsupervised Speckle Reduction of Optical Coherence Tomography Images Circadian variations in pathogenesis of ST-segment elevation myocardial infarction: an optical coherence tomography study