Conference Proceeding

ACHIKO-D350: A dataset for early AMD detection and drusen segmentation

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Abstract

Age related macular degeneration is the third leading cause of global blindness. Its prevalence is increasing in these years for the coming of ”aging population”. Early detection and grading can prevent it from becoming severe and protect vision. Drusen is an important indicator for AMD. Thus automatic drusen detection and segmentation has attracted much research attention in the past years. However, a barrier handicapping the research of drusen segmentation is the lack of a public dataset and test platform. To address this issue, in this paper, we publish a dataset, named ACHIKO-D350, with manually marked drusen boundary. ACHIKO-D350 includes 254 healthy fundus images and 96 fundus images with drusen. The images with drusen cover a wide range of types, including images with sparsely distributed drusen or clumped drusen, images of poor quality, and both well macular centered images and mis-centered images. ACHIKO-D350 will be used for performance evaluation of drusen segmentation methods. It will facilitate an objective evaluation and comparison.

How to Cite:

Liu, H. & Xu, Y. & Wong, D. W. & Laude, A. & Lim, T. H. & Liu, J., (2014) “ACHIKO-D350: A dataset for early AMD detection and drusen segmentation”, Proceedings of the Ophthalmic Medical Image Analysis International Workshop 1(2014), 73-80. doi: https://doi.org/10.17077/omia.1011

Rights: Copyright © 2014, Huiying Liu, Yanwu Xu, Damon W. K. Wong, Augustinus Laude, Tock Han Lim, and Jiang Liu.