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Anterior segment optical coherence tomography (AS-OCT) is a non-invasive imaging technique that is highly valuable for ophthalmic diagnosis.
“Multiplier and gradient methods,”
Magnus R Hestenes, · 1969
Earlier work this paper cites.
“Speckle in optical coherence tomography,”
Joseph M. Schmitt, S. H. Xiang, and Kin Man Yung, · 1999
Earlier work this paper cites.
“Real-time optical coherence tomography of the anterior segment at 1310 nm,”
Sunita Radhakrishnan, Andrew M Rollins, Jonathan E Roth, Siavash Yazdanfar, Volker Westphal, David S Bardenstein, and Joseph A Izatt, · 2001
Earlier work this paper cites.
“A non-local algorithm for image denoising,”
Antoni Buades, Bartomeu Coll, and J-M Morel, · 2005
Earlier work this paper cites.
“Automatic recovery of the optic nervehead geometry in optical coherence tomography,”
Kim L Boyer, Artemas Herzog, and Cynthia Roberts, · 2006
Earlier work this paper cites.
“A directional multiscale approach for speckle reduction in optical coherence tomography images,”
Mohamad Forouzanfar and Hamid Abrishami Moghaddam, · 2007
Earlier work this paper cites.
“Multiplicative noise removal using variable splitting and constrained optimization,”
José M Bioucas-Dias and Mário AT Figueiredo, · 2010
Earlier work this paper cites.
“Anterior chamber angle imaging with optical coherence tomography,”
C KS Leung and RN Weinreb, · 2012
Earlier work this paper cites.
“Making a “completely blind” image quality analyzer,”
Anish Mittal, Rajiv Soundararajan, and Alan C Bovik, · 2012
Earlier work this paper cites.
“Speckle reduction in optical coherence tomography images of human finger skin by wavelet modified bm3d filter,”
Bo Chong and Yong-Kai Zhu, · 2013
Earlier work this paper cites.
“Effective speckle noise suppression in optical coherence tomography images using nonlocal means denoising filter with double gaussian anisotropic kernels,”
Jaehong Aum, Ji-hyun Kim, and Jichai Jeong, · 2015
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Raheleh Kafieh, Hossein Rabbani, and Ivan Selesnick, · 2015
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Guangyong Chen, Fengyuan Zhu, and Pheng Ann Heng, · 2015
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“U-net: Convolutional networks for biomedical image segmentation,”
Olaf Ronneberger, Philipp Fischer, and Thomas Brox, · 2015
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“Statistical modeling of retinal optical coherence tomography,”
Zahra Amini and Hossein Rabbani, · 2016
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“Denoising diffusion probabilistic models,”
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“A newton solver for micromorphic computational homogenization enabling multiscale buckling analysis of pattern-transforming metamaterials,”
SEHM van Bree, O Rokoš, Ron HJ Peerlings, M Doškář, and Marc GD Geers, · 2020
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“Modeling of retinal optical coherence tomography based on stochastic differential equations: Application to denoising,”
Mahnoosh Tajmirriahi, Zahra Amini, Arsham Hamidi, Azhar Zam, and Hossein Rabbani, · 2021
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“Speckle2void: Deep self-supervised sar despeckling with blind-spot convolutional neural networks,”
Andrea Bordone Molini, Diego Valsesia, Giulia Fracastoro, and Enrico Magli, · 2021
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“Speckle2speckle: Unsupervised learning of ultrasound speckle filtering without clean data,”
Rüdiger Göbl, Christoph Hennersperger, and Nassir Navab, · 2022
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Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A Efros, · 2017
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Theodore B Dubose, David Cunefare, Elijah Cole, Peyman Milanfar, Joseph A Izatt, and Sina Farsiu, · 2017
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“Unsupervised image-to-image translation networks,”
Ming-Yu Liu, Thomas Breuel, and Jan Kautz, · 2017
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“Speckle noise reduction in optical coherence tomography images based on edge-sensitive cgan,”
Yuhui Ma, Xinjian Chen, Weifang Zhu, Xuena Cheng, Dehui Xiang, and Fei Shi, · 2018
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Taesung Park, Alexei A Efros, Richard Zhang, and Jun-Yan Zhu, · 2020
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“Unsupervised denoising of retinal oct with diffusion probabilistic model,”
Dewei Hu, Yuankai K Tao, and Ipek Oguz, · 2022
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“Reproducibility of deep learning based scleral spur localisation and anterior chamber angle measurements from anterior segment optical coherence tomography images,”
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