ACHIKO-M Database for high myopia analysis and its evaluation
- Fengshou Yin (Agency for Science, Technology and Research)
- Ruoying Li (Agency for Science, Technology and Research)
- Zhuo Zhang (Agency for Science, Technology and Research)
- Jun Cheng (Agency for Science, Technology and Research)
- Yanwu Xu (Agency for Science, Technology and Research)
- Damon Wee Kee Wong (Agency for Science, Technology and Research)
- Ngan Meng Tan (Agency for Science, Technology and Research)
- Ying Quan (Agency for Science, Technology and Research)
- Ai Ping Yow (Agency for Science, Technology and Research)
- Gopalakrishnan Kavitha (Agency for Science, Technology and Research)
- Guozhen Xu (Agency for Science, Technology and Research)
- Jiang Liu (Agency for Science, Technology and Research)
Abstract
Myopia is the leading public health concern with high prevalence in developed countries. In this paper, we present the ACHIKO-M fundus image database with both myopic and emmetropic cases for high myopia study. The database contains 705 myopic subjects and 151 normal subjects with both left eye and right eye images for each subject. In addition, various clinical data is also available, allowing correlation study of different risk factors. We evaluated two state-of-the-art automated myopia detection algorithms on this database to show how it can be used. Both methods achieve more than 90% accuracy for myopia diagnosis. We will also discuss how ACHIKO-M can be a good database for both scientific and clinical research of myopia.
How to Cite:
Yin, F. & Li, R. & Zhang, Z. & Cheng, J. & Xu, Y. & Wong, D. W. & Tan, N. M. & Quan, Y. & Yow, A. P. & Kavitha, G. & Xu, G. & Liu, J., (2014) “ACHIKO-M Database for high myopia analysis and its evaluation”, Proceedings of the Ophthalmic Medical Image Analysis International Workshop 1(2014), 121-128. doi: https://doi.org/10.17077/omia.1017
Rights: Copyright © 2014, Fengshou Yin, Ruoying Li, Zhuo Zhang, Jun Cheng, Yanwu Xu, Damon Wee Kee Wong, Ngan Meng Tan, Ying Quan, Ai Ping Yow, Gopalakrishnan Kavitha, Guozhen Xu, and Jiang Liu.
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