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Literature DB >> 33654681

Artifacts and artifact removal in optical coherence tomographic angiography.

Tristan T Hormel¹, David Huang¹, Yali Jia^1,2.

Abstract

Optical coherence tomographic angiography (OCTA) enables rapid imaging of retinal vasculature in three dimensions. While the technique has provided quantification of healthy vessels as well as pathology in several diseases, it is not unusual for OCTA data to contain artifacts that may influence measurement outcomes or defy image interpretation. In this review, we discuss the sources of several OCTA artifacts-including projection, motion, and signal reduction-as well as strategies for their removal. Artifact compensation can improve the accuracy of OCTA measurements, and the most effective use of the technology will incorporate hardware and software that can perform such correction. 2021 Quantitative Imaging in Medicine and Surgery. All rights reserved.

Keywords: Optical coherence tomographic angiography (OCTA); artifact correction; imaging artifacts

Year: 2021 PMID： 33654681 PMCID： PMC7829161 DOI： 10.21037/qims-20-730

Source DB: PubMed Journal: Quant Imaging Med Surg ISSN： 2223-4306

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Cited

8 in total

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2. A Workflow for Three-Dimensional Reconstruction and Quantification of the Monkey Optic Nerve Head Vascular Network.

Authors: Po-Yi Lee; Yi Hua; Bryn L Brazile; Bin Yang; Lin Wang; Ian A Sigal
Journal: J Biomech Eng Date: 2022-06-01 Impact factor: 1.899

3. Detection of the Microvascular Changes of Diabetic Retinopathy Progression Using Optical Coherence Tomography Angiography.

Authors: Xiaogang Wang; Yongqing Han; Gang Sun; Fang Yang; Wen Liu; Jing Luo; Xing Cao; Pengyi Yin; Frank L Myers; Liang Zhou
Journal: Transl Vis Sci Technol Date: 2021-06-01 Impact factor: 3.283

4. An Open-Source Deep Learning Network for Reconstruction of High-Resolution OCT Angiograms of Retinal Intermediate and Deep Capillary Plexuses.

Authors: Min Gao; Tristan T Hormel; Jie Wang; Yukun Guo; Steven T Bailey; Thomas S Hwang; Yali Jia
Journal: Transl Vis Sci Technol Date: 2021-11-01 Impact factor: 3.283

Artifacts and artifact removal in optical coherence tomographic angiography.

1. Real-time OCT image denoising using a self-fusion neural network.

2. A Workflow for Three-Dimensional Reconstruction and Quantification of the Monkey Optic Nerve Head Vascular Network.

3. Detection of the Microvascular Changes of Diabetic Retinopathy Progression Using Optical Coherence Tomography Angiography.

4. An Open-Source Deep Learning Network for Reconstruction of High-Resolution OCT Angiograms of Retinal Intermediate and Deep Capillary Plexuses.

5. Pulsatile tissue deformation dynamics of the murine retina and choroid mapped by 4D optical coherence tomography.

Review 6. Towards standardizing retinal optical coherence tomography angiography: a review.

7. A Diabetic Retinopathy Classification Framework Based on Deep-Learning Analysis of OCT Angiography.

8. Retinal microvasculature alteration in patients with systemic sclerosis and chloroquine treatment.