Robust Collaborative Learning of Patch-Level and Image-Level Annotations for Diabetic Retinopathy Grading From Fundus Image
文献类型：期刊论文
| 作者 | Yang, Yehui3 ; Shang, Fangxin3; Wu, Binghong3; Yang, Dalu3; Wang, Lei3; Xu, Yanwu3; Zhang, Wensheng1; Zhang, Tianzhu2
|
| 刊名 | IEEE TRANSACTIONS ON CYBERNETICS
 |
| 出版日期 | 2021-05-07 |
| 页码 | 11 |
| 关键词 | Lesions Annotations Generators Feature extraction Image segmentation Retinopathy Diabetes Collaborative learning convolutional neural networks (CNNs) diabetic retinopathy (DR) fundus image |
| ISSN号 | 2168-2267 |
| DOI | 10.1109/TCYB.2021.3062638 |
| 通讯作者 | Xu, Yanwu(ywxu@ieee.org) |
| 英文摘要 | Diabetic retinopathy (DR) grading from fundus images has attracted increasing interest in both academic and industrial communities. Most convolutional neural network-based algorithms treat DR grading as a classification task via image-level annotations. However, these algorithms have not fully explored the valuable information in the DR-related lesions. In this article, we present a robust framework, which collaboratively utilizes patch-level and image-level annotations, for DR severity grading. By an end-to-end optimization, this framework can bidirectionally exchange the fine-grained lesion and image-level grade information. As a result, it exploits more discriminative features for DR grading. The proposed framework shows better performance than the recent state-of-the-art algorithms and three clinical ophthalmologists with over nine years of experience. By testing on datasets of different distributions (such as label and camera), we prove that our algorithm is robust when facing image quality and distribution variations that commonly exist in real-world practice. We inspect the proposed framework through extensive ablation studies to indicate the effectiveness and necessity of each motivation. The code and some valuable annotations are now publicly available. |
| WOS研究方向 | Automation & Control Systems ; Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000732884800001 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://ir.ia.ac.cn/handle/173211/46914]  |
| 专题 | 精密感知与控制研究中心_人工智能与机器学习 |
| 通讯作者 | Xu, Yanwu |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 2.Univ Sci & Technol China, Sch Data Sci, Hefei 230027, Peoples R China 3.Baidu Inc, Intelligent Healthcare Unit, Artificial Intelligence Cloud Grp, Beijing 100085, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yang, Yehui,Shang, Fangxin,Wu, Binghong,et al. Robust Collaborative Learning of Patch-Level and Image-Level Annotations for Diabetic Retinopathy Grading From Fundus Image[J]. IEEE TRANSACTIONS ON CYBERNETICS,2021:11. |
| APA | Yang, Yehui.,Shang, Fangxin.,Wu, Binghong.,Yang, Dalu.,Wang, Lei.,...&Zhang, Tianzhu.(2021).Robust Collaborative Learning of Patch-Level and Image-Level Annotations for Diabetic Retinopathy Grading From Fundus Image.IEEE TRANSACTIONS ON CYBERNETICS,11. |
| MLA | Yang, Yehui,et al."Robust Collaborative Learning of Patch-Level and Image-Level Annotations for Diabetic Retinopathy Grading From Fundus Image".IEEE TRANSACTIONS ON CYBERNETICS (2021):11. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。