1. Articles from Lei Zhu

    1-4 of 4
    1. Triplet Cross-Fusion Learning for Unpaired Image Denoising in Optical Coherence Tomography

      Triplet Cross-Fusion Learning for Unpaired Image Denoising in Optical Coherence Tomography

      Optical coherence tomography (OCT) is a widely-used modality in clinical imaging, which suffers from the speckle noise inevitably. Deep learning has proven its superior capability in OCT image denoising, while the difficulty of acquiring a large number of well-registered OCT image pairs limits the developments of paired learning methods. To solve this problem, some unpaired learning methods have been proposed, where the denoising networks can be trained with unpaired OCT data. However, majority of them are modified from the cycleGAN framework. These cycleGAN-based methods train at least two generators and two discriminators, while only one generator is needed for the ...

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    2. Rethinking the neighborhood information for deep learning-based optical coherence tomography angiography

      Rethinking the neighborhood information for deep learning-based optical coherence tomography angiography

      Purpose: Optical coherence tomography angiography (OCTA) is a premium imaging modality for non-invasive microvasculature studies. Deep learning networks have achieved promising results in the OCTA reconstruction task, benefiting from their powerful modeling capability. However, two limitations exist in the current deep learning-based OCTA reconstruction methods: 1) the angiogram information extraction is only limited to the locally consecutive B-scans; 2) all reconstruction models are confined to the 2D convolutional network architectures, lacking effective temporal modeling. As a result, the valuable neighborhood information and inherent temporal characteristics of OCTA are not fully utilized. In this paper, we designed a neighborhood-information-fused Pseudo-3D U-Net ...

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    3. Automated Analysis of Choroidal Sublayer Morphologic Features in Myopic Children Using EDI-OCT by Deep Learning

      Automated Analysis of Choroidal Sublayer Morphologic Features in Myopic Children Using EDI-OCT by Deep Learning

      Purpose: The purpose of this study was to analyze the choroidal sublayer morphologic features in emmetropic and myopic children using an automatic segmentation model, and to explore the relationship between choroidal sublayers and spherical equivalent refraction (SER). Methods: We collected data on 92 healthy children (92 eyes) from the Ophthalmology Department of Peking University First Hospital. The data were allocated to three groups: emmetropia (+0.50 diopters [D] to -0.50 D), low myopia (-0.75 D to -3.00 D), and moderate myopia (-3.25 D to -5.75 D). We performed standardized optical coherence tomography (OCT) and developed ...

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    4. Prediction of spontaneous closure of traumatic macular hole with spectral domain optical coherence tomography

      Prediction of spontaneous closure of traumatic macular hole with spectral domain optical coherence tomography

      It has been known that some traumatic macular holes can close spontaneously. However, knowledge about the types of macular hole that can close spontaneously is limited. In this retrospective study, we investigated patients with traumatic macular hole who were followed-up for at least 6 months without any surgical intervention. Clinical data and spectral domain optical coherence tomography (SD-OCT) images were compared between groups with and without macular hole closure. Overall, 27 eyes were included. Spontaneous closure of macular hole was observed in 10 (37.0%) eyes. The holes with spontaneous closure had smaller minimum diameter (244.9 ± 114.4 vs ...

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    1-4 of 4
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    1. (2 articles) Peking University
    2. (1 articles) The Chinese University of Hong Kong
    3. (1 articles) FDA
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    Prediction of spontaneous closure of traumatic macular hole with spectral domain optical coherence tomography Automated Analysis of Choroidal Sublayer Morphologic Features in Myopic Children Using EDI-OCT by Deep Learning Rethinking the neighborhood information for deep learning-based optical coherence tomography angiography Triplet Cross-Fusion Learning for Unpaired Image Denoising in Optical Coherence Tomography Cascade Optical Coherence Tomography (C-OCT) for Surface Form Metrology of - ProQuest Comparison of Anterior Segment Measurements with a New Multifunctional Unit and Five Other Devices Efficacy of Notal Vision Home OCT demonstrated by a series of scientific and clinical work Synergy Between morpHOlogical and inflammatoRy Evaluation in Predicting Long-term Coronary Plaque Progression Altered ocular microvasculature in patients with systemic sclerosis and very early disease of systemic sclerosis using optical coherence tomography angiography Assessment of macular findings by OCT angiography in patients without clinical signs of diabetic retinopathy: radiomics features for early screening of diabetic retinopathy Self-Examination Low-Cost Full-Field Optical Coherence Tomography (SELFF-OCT) for neovascular age-related macular degeneration: a cross-sectional diagnostic accuracy study The Use of Optical Coherence Tomography to Demonstrate Dark and Light Adaptation in a Live Moth