ArticleBiomedical optics express2018
Speckle noise reduction in optical coherence tomography images based on edge-sensitive cGAN.
Article in Biomedical optics express, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 1 of them a synthesis that pooled it.
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Who cites it
63 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Ophthalmic Image Synthesis and Analysis with Generative Adversarial Network Artificial Intelligence.Journal of imaging informatics in medicine · 2026Pooled it
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- PSB-DSN: a two-stage unsupervised denoising enhancement network for OCT images based on pixel shuffle and blind spot masking.Biomedical optics express · 2026Article
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- Enhancement of Optical Coherence Tomography Images Using Adversarial Neural Networks: Impacts on Ophthalmic Practice.Cureus · 2025Article
- Self-supervised model-informed deep learning for low-SNR SS-OCT domain transformation.Scientific reports · 2025Article
- Complex conjugate removal in optical coherence tomography using phase aware generative adversarial network.Journal of biomedical optics · 2025Article
- Reconstruction of Optical Coherence Tomography Images from Wavelength Space Using Deep Learning.Sensors (Basel, Switzerland) · 2024Article
- Sample tilting for speckle suppression through angular compounding.Optics letters · 2024Article
- Probabilistic volumetric speckle suppression in OCT using deep learning.Biomedical optics express · 2024Article
- Sub2Full: split spectrum to boost optical coherence tomography despeckling without clean data.Optics letters · 2024Article
- Brain tumor grading diagnosis using transfer learning based on optical coherence tomography.Biomedical optics express · 2024Article
- Denoising of Optical Coherence Tomography Images in Ophthalmology Using Deep Learning: A Systematic Review.Journal of imaging · 2024Review
- Denoising OCT videos based on temporal redundancy.Scientific reports · 2024Article
- Super-resolution of Retinal Optical Coherence Tomography Images Using Statistical Modeling.Journal of medical signals and sensors · 2024Article
- Machine Learning-Assisted Short-Wave InfraRed (SWIR) Techniques for Biomedical Applications: Towards Personalized Medicine.Journal of personalized medicine · 2023Review
- Article
3 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Speckle noise in optical coherence tomography (OCT) impairs both the visual quality and the performance of automatic analysis. Edge preservation is an important issue for speckle reduction. In this paper, we propose an end-to-end framework for simultaneous speckle reduction and contrast enhancement for retinal OCT images based on the conditional generative adversarial network (cGAN). The edge loss function is added to the final objective so that the model is sensitive to the edge-related details. We also propose a novel method for obtaining clean images for training from outputs of commercial OCT scanners. The results show that the overall denoising performance of the proposed method is better than other traditional methods and deep learning methods. The proposed model also has good generalization ability and is capable of despeckling different types of retinal OCT images.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.