1. Articles from Paria Jeihouni

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    1. MultiSDGAN: translation of OCT images to superresolved segmentation labels using multi-discriminators in multi-stages

      MultiSDGAN: translation of OCT images to superresolved segmentation labels using multi-discriminators in multi-stages

      Optical coherence tomography (OCT) has been identified as a non-invasive and inexpensive imaging modality to discover potential biomarkers for Alzheimer's diagnosis and progress determination. Current hypotheses presume the thickness of the retinal layers, which are analyzable within OCT scans, as an effective biomarker for the presence of Alzheimer's. As a logical first step, this work concentrates on the accurate segmentation of retinal layers to isolate the layers for further analysis. This paper proposes a generative adversarial network (GAN) that concurrently learns to increase the image resolution for higher clarity and then segment the retinal layers. We propose a ...

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    1. (1 articles) Kyoto University Graduate School of Medicine
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