Automated Cone Cell Identification on Adaptive Optics Scanning Laser Ophthalmoscope Images Based on...
Automated Cone Cell Identification on Adaptive Optics Scanning Laser Ophthalmoscope Images Based on TV-L1 Optical Flow Registration and K-Means Clustering
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Author / Creator
Chen, Yiwei , He, Yi , Wang, Jing , Li, Wanyue , Xing, Lina , Zhang, Xin and Shi, Guohua
Publisher
Basel: MDPI AG
Journal title
Language
English
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Publication information
Publisher
Basel: MDPI AG
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Contents
Cone cell identification is essential for diagnosing and studying eye diseases. In this paper, we propose an automated cone cell identification method that involves TV-L1 optical flow estimation and K-means clustering. The proposed algorithm consists of the following steps: image denoising based on TV-L1 optical flow registration, bias field correc...
Alternative Titles
Full title
Automated Cone Cell Identification on Adaptive Optics Scanning Laser Ophthalmoscope Images Based on TV-L1 Optical Flow Registration and K-Means Clustering
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Author / Creator
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_3e157a802d7941b985285f823425c9fb
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_3e157a802d7941b985285f823425c9fb
Other Identifiers
ISSN
2076-3417
E-ISSN
2076-3417
DOI
10.3390/app11052259
