Knowledge Commons of Institute of Automation,CAS
Spatial non-local attention for thoracic disease diagnosis and visualisation in weakly supervised learning | |
Yang, Menglin1,2; Li, Ding1; Zhang, Wensheng1,2 | |
发表期刊 | IET IMAGE PROCESSING |
ISSN | 1751-9659 |
2019-09-19 | |
卷号 | 13期号:11页码:1922-1930 |
通讯作者 | Zhang, Wensheng(zhangwenshengia@hotmail.com) |
摘要 | Weakly supervised learning is capable of achieving fine-grained tasks with coarse annotations, which has shown great potential in computer-aided diagnosis. This study aims to achieve thoracic disease diagnosis in a weakly supervised manner only with coarse image-level annotations. Except for considering the performance of disease diagnosis, the study concentrates more on discovering the location of the pathological area which is used as visualised evidence for interpretability of diagnosis and the following retrospective analysis. To harvest more associated pathological areas, spatial non-local attention mechanism to learn non-local aware features is investigated. Further, a simple, effective, and widely applicable model ResNet-spatial non-local attention (SNA) is developed for these two objectives. Besides, an effective visualisation method compatible with the proposal is introduced. The effectiveness of the proposed ResNet-SNA was validated on the large publicly available chest X-ray dataset, ChestX-ray14. Compared with the baseline model, the proposed model improved by 7.96% averaged over 14 diseases, achieving 0.8247 area under the scores up to the highest classification results compared with related works. For localisation, the proposed model improved the performance significantly without using any extra information. More importantly, the proposal only requires image-level annotations without fine-grained expertise, which is cost-effective and expected to apply in clinical diagnosis. |
关键词 | feature extraction diseases medical image processing patient diagnosis image segmentation image classification supervised learning image annotation thoracic disease diagnosis weakly supervised learning computer-aided diagnosis coarse image-level annotations pathological area nonlocal aware features fine-grained expertise clinical diagnosis visualisation method chest X-ray dataset spatial nonlocal attention mechanism ResNet-SNA |
DOI | 10.1049/iet-ipr.2019.0032 |
关键词[WOS] | IMAGE SEGMENTATION |
收录类别 | SCI |
语种 | 英语 |
资助项目 | Beijing Natural Science Foundation[4172063] ; National Natural Science Foundation of China[61876183] ; National Natural Science Foundation of China[61602484] ; National Natural Science Foundation of China[61472423] ; National Natural Science Foundation of China[U1636220] ; National Natural Science Foundation of China[U1636220] ; National Natural Science Foundation of China[61472423] ; National Natural Science Foundation of China[61602484] ; National Natural Science Foundation of China[61876183] ; Beijing Natural Science Foundation[4172063] |
项目资助者 | National Natural Science Foundation of China ; Beijing Natural Science Foundation |
WOS研究方向 | Computer Science ; Engineering ; Imaging Science & Photographic Technology |
WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Imaging Science & Photographic Technology |
WOS记录号 | WOS:000487789000014 |
出版者 | INST ENGINEERING TECHNOLOGY-IET |
七大方向——子方向分类 | 人工智能+医疗 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/26981 |
专题 | 多模态人工智能系统全国重点实验室_人工智能与机器学习(杨雪冰)-技术团队 |
通讯作者 | Zhang, Wensheng |
作者单位 | 1.Chinese Acad Sci, Res Ctr Precis Sensing & Control, Inst Automat, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Coll Artificial Intelligence, Beijing 101408, Peoples R China |
第一作者单位 | 精密感知与控制研究中心 |
通讯作者单位 | 精密感知与控制研究中心 |
推荐引用方式 GB/T 7714 | Yang, Menglin,Li, Ding,Zhang, Wensheng. Spatial non-local attention for thoracic disease diagnosis and visualisation in weakly supervised learning[J]. IET IMAGE PROCESSING,2019,13(11):1922-1930. |
APA | Yang, Menglin,Li, Ding,&Zhang, Wensheng.(2019).Spatial non-local attention for thoracic disease diagnosis and visualisation in weakly supervised learning.IET IMAGE PROCESSING,13(11),1922-1930. |
MLA | Yang, Menglin,et al."Spatial non-local attention for thoracic disease diagnosis and visualisation in weakly supervised learning".IET IMAGE PROCESSING 13.11(2019):1922-1930. |
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