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  • Received: Mar. 21, 2020

    Accepted: Jun. 1, 2020

    Posted: Jul. 31, 2020

    Published Online: Aug. 5, 2020

    The Author Email: Guohua Shi (ghshi_lab@126.com)

    DOI: 10.3788/COL202018.101701

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    Yiwei Chen, Yi He, Jing Wang, Wanyue Li, Lina Xing, Feng Gao, Guohua Shi. Automated superpixels-based identification and mosaicking of cone photoreceptor cells for adaptive optics scanning laser ophthalmoscope[J]. Chinese Optics Letters, 2020, 18(10): 101701

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Chinese Optics Letters, Vol. 18, Issue 10, 101701 (2020)

Automated superpixels-based identification and mosaicking of cone photoreceptor cells for adaptive optics scanning laser ophthalmoscope

Yiwei Chen1, Yi He1, Jing Wang1,2, Wanyue Li1,2, Lina Xing1, Feng Gao1, and Guohua Shi1,2,3,*

Author Affiliations

  • 1Jiangsu Key Laboratory of Medical Optics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
  • 2Department of Biomedical Engineering, University of Science and Technology of China, Hefei 230041, China
  • 3Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China

Abstract

An automated superpixels identification/mosaicking method is presented for the analysis of cone photoreceptor cells with the use of adaptive optics scanning laser ophthalmoscope (AO-SLO) images. This is an image oversegmentation method used for the identification and mosaicking of cone photoreceptor cells in AO-SLO images. It includes image denoising, estimation of the cone photoreceptor cell number, superpixels segmentation, merging of superpixels, and final identification and mosaicking processing steps. The effectiveness of the presented method was confirmed based on its comparison with a manual method in terms of precision, recall, and F1-score of 77.3%, 95.2%, and 85.3%, respectively.

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