1. Articles from Matthew H. Lee

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    1. Retinal optical coherence tomography image enhancement via deep learning

      Retinal optical coherence tomography image enhancement via deep learning

      Optical coherence tomography (OCT) images of the retina are a powerful tool for diagnosing and monitoring eye disease. However, they are plagued by speckle noise, which reduces image quality and reliability of assessment. This paper introduces a novel speckle reduction method inspired by the recent successes of deep learning in medical imaging. We present two versions of the network to reflect the needs and preferences of different end-users. Specifically, we train a convolution neural network to denoise cross-sections from OCT volumes of healthy eyes using either (1) mean-squared error, or (2) a generative adversarial network (GAN) with Wasserstein distance and ...

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  2. Topics in the News

    1. (1 articles) NYU Langone Medical Center
    2. (1 articles) Hiroshi Ishikawa
    3. (1 articles) Gadi Wollstein
    4. (1 articles) Joel S. Schuman
    5. (1 articles) University of Sydney
    6. (1 articles) University of Zurich
    7. (1 articles) UCSD
    8. (1 articles) University of Pittsburgh
    9. (1 articles) L V Prasad Eye Institute
    10. (1 articles) Giuseppe Querques
    11. (1 articles) Carl Zeiss Meditec
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