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OPHTHALMIC IMAGE
Year : 2020  |  Volume : 68  |  Issue : 10  |  Page : 2251

High-contrast scleroconjunctival microvasculature via deep learning denoising


Department of Ophthalmology, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan

Date of Web Publication23-Sep-2020

Correspondence Address:
Dr. Akitaka Tsujikawa
Department of Ophthalmology, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto 606-8507
Japan
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijo.IJO_1079_20

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How to cite this article:
Kadomoto S, Uji A, Muraoka Y, Tsujikawa A. High-contrast scleroconjunctival microvasculature via deep learning denoising. Indian J Ophthalmol 2020;68:2251

How to cite this URL:
Kadomoto S, Uji A, Muraoka Y, Tsujikawa A. High-contrast scleroconjunctival microvasculature via deep learning denoising. Indian J Ophthalmol [serial online] 2020 [cited 2020 Oct 30];68:2251. Available from: https://www.ijo.in/text.asp?2020/68/10/2251/295656



Anterior segment optical coherence tomography angiography (AS-OCTA) is a newly developed technique for noninvasive imaging of blood flow, including the scleroconjunctival microvasculature and iris.[1],[2] However, AS-OCTA images frequently have background noise because the OCTA devices were developed specially for retinal imaging. The left eye of a 45-year-old healthy individual of AS-OCTA image [Figure 1]a provides a scleroconjunctival microvasculature with significant background noise. A high-contrast image [Figure 1]b and [Figure 1]c is produced by applying deep learning-based denoising method (Intelligent denoise, Canon, Inc, Tokyo, Japan).[3] Panoramic high-contrast AS-OCTA image [Figure 1]c processed with deep learning-based denoising is useful to evaluate circumferential conjunctival vasculature.
Figure 1: Swept-source anterior segment-optical coherence tomography angiography (AS-OCTA) images (OCT S1: Canon, Inc, Tokyo, Japan). To visualize the conjunctival and deep scleral vessels, a 400-μm thick slab of the conjunctival surface was selected. Seven AS-OCTA images were used to reconstruct a panoramic image.

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Declaration of patient consent

The authors certify that they have obtained all appropriate patient consent forms. In the form the patient(s) has/have given his/her/their consent for his/her/their images and other clinical information to be reported in the journal. The patients understand that their names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Kadomoto S, Uji A, Tsujikawa A. Anterior segment optical coherence tomography angiography in a patient with persistent pupillary membrane. JAMA Ophthalmol2018;136:e182932.  Back to cited text no. 1
    
2.
Akagi T, Uji A, Huang AS, Weinreb RN, Yamada T, Miyata M, et al. Conjunctival and intrascleral vasculatures assessed using anterior segment optical coherence tomography angiography in normal eyes. Am J Ophthalmol2018;196:1-9.  Back to cited text no. 2
    
3.
Kadomoto S, Uji A, Muraoka Y, Akagi T, Tsujikawa A. Enhanced visualization of retinal microvasculature in optical coherence tomography angiography imaging via deep learning. J Clin Med2020;9. doi: 10.3390/jcm9051322.  Back to cited text no. 3
    


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