1. Articles from Lixin Duan

    1-4 of 4
    1. Reproducibility of deep learning based scleral spur localisation and anterior chamber angle measurements from anterior segment optical coherence tomography images

      Reproducibility of deep learning based scleral spur localisation and anterior chamber angle measurements from anterior segment optical coherence tomography images

      Aims: To apply a deep learning model for automatic localisation of the scleral spur (SS) in anterior segment optical coherence tomography (AS-OCT) images and compare the reproducibility of anterior chamber angle (ACA) width between deep learning located SS (DLLSS) and manually plotted SS (MPSS). Methods: In this multicentre, cross-sectional study, a test dataset comprising 5166 AS-OCT images from 287 eyes (116 healthy eyes with open angles and 171 eyes with primary angle-closure disease (PACD)) of 287 subjects were recruited from four ophthalmology clinics. Each eye was imaged twice by a swept-source AS-OCT (CASIA2, Tomey, Nagoya, Japan) in the same visit ...

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    2. Axial Alignment for Anterior Segment Swept Source Optical Coherence Tomography via Robust Low-Rank Tensor Recovery

      Axial Alignment for Anterior Segment Swept Source Optical Coherence Tomography via Robust Low-Rank Tensor Recovery

      We present a one-step approach based on low-rank tensor recovery for axial alignment in 360-degree anterior chamber optical coherence tomography. Achieving translational alignment and rotation correction of cross-sections simultaneously, this technique obtains a better anterior segment topographical representation and improves quantitative measurement accuracy and reproducibility of disease related parameters. Through its use of global information, the proposed method is more robust compared to using only individual or paired slices, and less sensitive to noise and motion artifacts. In angle closure analysis on 30 patient eyes, the preliminary results indicate that the proposed axial alignment method can not only facilitate manual ...

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    3. Speckle reduction in optical coherence tomography by matrix completion using bilateral random projection

      Speckle reduction in optical coherence tomography by matrix completion using bilateral random projection

      Speckle noise is problematic in optical coherence tomography (OCT) and often obscures the structure details. In this paper, we propose a new method to reduce speckle noise from multiply scanned OCT slices. The proposed method registers the OCT scans using a global alignment followed by a local alignment based on global and local motion estimation. Then low rank matrix completion using bilateral random projection is utilized to estimate the noise and recover the clean image. Experimental results show that the proposed method archives average contrast to noise ratio 14.90, better than 13.78 by the state-of-the-art method used in ...

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    4. Speckle Reduction in Optical Coherence Tomography by Image Registration and Matrix Completion

      Speckle Reduction in Optical Coherence Tomography by Image Registration and Matrix Completion

      Speckle noise is problematic in optical coherence tomography (OCT). With the fast scan rate, swept source OCT scans the same position in the retina for multiple times rapidly and computes an average image from the multiple scans for speckle reduction. However, the eye movement poses some challenges. In this paper, we propose a new method for speckle reduction from multiply-scanned OCT slices. The proposed method applies a preliminary speckle reduction on the OCT slices and then registers them using a global alignment followed by a local alignment based on fast iterative diamond search. After that, low rank matrix completion using ...

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    1-4 of 4
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  2. Topics in the News

    1. (2 articles) Topcon Medical Systems
    2. (1 articles) University of Hong Kong
    3. (1 articles) Harvard University
    4. (1 articles) University College London
    5. (1 articles) Brigham and Women’s Hospital
    6. (1 articles) Tomey Corporation
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