Quantitative analysis of deep learning-based denoising model efficacy on optical coherence tomography images with different noise levels-Reference-Cited by-同舟云学术

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Quantitative analysis of deep learning-based denoising model efficacy on optical coherence tomography images with different noise levels

Published:2024-02 Issue: Volume:45 Page:103891
ISSN:1572-1000
Container-title:Photodiagnosis and Photodynamic Therapy
language:en
Short-container-title:Photodiagnosis and Photodynamic Therapy

Author:

Kirik Furkan^ORCID,Iskandarov Farid,Erturk Kamile Melis,Ozdemir Hakan

Publisher

Elsevier BV

Subject

Pharmacology (medical),Dermatology,Oncology,Biophysics

Reference40 articles.

1. Optical coherence tomography;Huang;Science,1991

2. Optical coherence tomography—A review of the principles and contemporary uses in retinal investigation;Thomas;Eye,2004

3. Enhanced depth imaging spectral-domain optical coherence tomography;Spaide;Am. J. Ophthalmol.,2008

4. Optical coherence tomography's current clinical medical and dental applications: a review;Ali;F1000Res,2021

5. Optical coherence tomography: an introduction to the technique and its use;Hrynchak;Optom. Vis. Sci.,2000

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