Pixel-wise segmentation of severely pathologic retinal pigment epithelium and choroidal stroma using multi-contrast Jones matrix optical coherence tomography

Shinnosuke Azuma; Shuichi Makita; Arata Miyazawa; Yasushi Ikuno; Masahiro Miura; Yoshiaki Yasuno

doi:10.1364/BOE.9.002955

Pixel-wise segmentation of severely pathologic retinal pigment epithelium and choroidal stroma using multi-contrast Jones matrix optical coherence tomography

Biomed Opt Express. 2018 Jun 6;9(7):2955-2973. doi: 10.1364/BOE.9.002955. eCollection 2018 Jul 1.

Authors

Shinnosuke Azuma^{1

2}, Shuichi Makita^{1

2}, Arata Miyazawa^{1

2}, Yasushi Ikuno³, Masahiro Miura^{2

4}, Yoshiaki Yasuno^{1

2}

Affiliations

¹ Computational Optics Group, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan.
² Computational Optics and Ophthalmology Group, Tsukuba, Ibaraki 305-8531, Japan.
³ Ikuno Eye Center, 2-9-10-3F Juso-Higashi, Yodogawa-Ku, Osaka 532-0023, Japan.
⁴ Tokyo Medical University Ibaraki Medical Center, 3-20-1 Chuo, Ami, Ibaraki 300-0395, Japan.

Abstract

Tissue segmentation of retinal optical coherence tomography (OCT) is widely used in ophthalmic diagnosis. However, its performance in severe pathologic cases is still insufficient. We propose a pixel-wise segmentation method that uses the multi-contrast measurement capability of Jones matrix OCT (JM-OCT). This method is applicable to both normal and pathologic retinal pigment epithelium (RPE) and choroidal stroma. In this method, "features," which are sensitive to specific tissues of interest, are synthesized by combining the multi-contrast images of JM-OCT, including attenuation coefficient, degree-of-polarization-uniformity, and OCT angiography. The tissue segmentation is done by simple thresholding of the feature. Compared with conventional segmentation methods for pathologic maculae, the proposed method is less computationally intensive. The segmentation method was validated by applying it to images from normal and severely pathologic cases. The segmentation results enabled the development of several types of en face visualizations, including melano-layer thickness maps, RPE elevation maps, choroidal thickness maps, and choroidal stromal attenuation coefficient maps. These facilitate close examination of macular pathology. The melano-layer thickness map is very similar to a near infrared fundus autofluorescence image, so the map can be used to identify the source of a hyper-autofluorescent signal.

Keywords: (100.2960) Image analysis; (110.4500) Optical coherence tomography; (170.4470) Ophthalmology; (170.4500) Optical coherence tomography; (170.5755) Retina scanning; (170.6935) Tissue characterization.