Quantitative Characterization of Retinal Features in Translated OCTA

Autor: Badhon, Rashadul Hasan, Thompson, Atalie Carina, Lim, Jennifer I., Leng, Theodore, Alam, Minhaj Nur

Purpose: This study explores the feasibility of using generative machine learning (ML) to translate Optical Coherence Tomography (OCT) images into Optical Coherence Tomography Angiography (OCTA) images, potentially bypassing the need for specialized

Externí odkaz: http://arxiv.org/abs/2404.16133

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Autor: Thompson, Atalie Carina, El-Dairi, Mays A.

Publikováno v: In Journal of AAPOS June 2018 22(3):248-249

Quantitative characterization of retinal features in translated OCTA.

Autor: Badhon RH; Department of Electrical and Computer Engineering, University of North Carolina at Charlotte, Charlotte, NC, United States., Thompson AC; Department of Surgical Ophthalmology, Atrium-Health Wake Forest Baptist, Winston-Salem, NC, United States., Lim JI; Department of Ophthalmology and Visual Science, University of Illinois at Chicago, Chicago, IL, United States., Leng T; Department of Ophthalmology, Stanford University School of Medicine, Stanford, CA, United States., Alam MN; Department of Electrical and Computer Engineering, University of North Carolina at Charlotte, Charlotte, NC, United States.

Publikováno v: Experimental biology and medicine (Maywood, N.J.) [Exp Biol Med (Maywood)] 2024 Oct 23; Vol. 249, pp. 10333. Date of Electronic Publication: 2024 Oct 23 (Print Publication: 2024).