arXiv Open Access 2020

Machine Learning for Cataract Classification and Grading on Ophthalmic Imaging Modalities: A Survey

Xiaoqing Zhang Yan Hu Zunjie Xiao Jiansheng Fang Risa Higashita +1 lainnya

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Abstrak

Cataracts are the leading cause of visual impairment and blindness globally. Over the years, researchers have achieved significant progress in developing state-of-the-art machine learning techniques for automatic cataract classification and grading, aiming to prevent cataracts early and improve clinicians' diagnosis efficiency. This survey provides a comprehensive survey of recent advances in machine learning techniques for cataract classification/grading based on ophthalmic images. We summarize existing literature from two research directions: conventional machine learning methods and deep learning methods. This survey also provides insights into existing works of both merits and limitations. In addition, we discuss several challenges of automatic cataract classification/grading based on machine learning techniques and present possible solutions to these challenges for future research.

Topik & Kata Kunci

eess.IV cs.CV cs.LG

Penulis (6)

Xiaoqing Zhang

Yan Hu

Zunjie Xiao

Jiansheng Fang

Risa Higashita

Jiang Liu

Format Sitasi

APA MLA BibTeX

Zhang, X., Hu, Y., Xiao, Z., Fang, J., Higashita, R., Liu, J. (2020). Machine Learning for Cataract Classification and Grading on Ophthalmic Imaging Modalities: A Survey. https://arxiv.org/abs/2012.04830

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Informasi Jurnal

Tahun Terbit: 2020
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓