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Presentation + Paper
10 March 2020 Self-fusion for OCT noise reduction
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Reducing speckle noise is an important task for improving visual and automated assessment of retinal OCT images. Traditional image/signal processing methods only offer moderate speckle reduction; deep learning methods can be more effective but require substantial training data, which may not be readily available. We present a novel self-fusion method that offers effective speckle reduction comparable to deep learning methods, but without any external training data. We present qualitative and quantitative results in a variety of datasets from fovea and optic nerve head regions, with varying SNR values for input images.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ipek Oguz, Joseph D. Malone, Yigit Atay, and Yuankai K. Tao "Self-fusion for OCT noise reduction", Proc. SPIE 11313, Medical Imaging 2020: Image Processing, 113130C (10 March 2020);

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