Computer-aided Tuberculosis Diagnosis with Attribute Reasoning Assistance

• URL: http://arxiv.org/abs/2207.00251v1
• Date: Fri, 1 Jul 2022 07:50:35 GMT
• Title: Computer-aided Tuberculosis Diagnosis with Attribute Reasoning Assistance
• Authors: Chengwei Pan, Gangming Zhao, Junjie Fang, Baolian Qi, Jiaheng Liu, Chaowei Fang, Dingwen Zhang, Jinpeng Li, and Yizhou Yu
• Abstract summary: We propose a new large-scale tuberculosis (TB) chest X-ray dataset (TBX-Att) We establish an attribute-assisted weakly-supervised framework to classify and localize TB by leveraging the attribute information. The proposed model is evaluated on the TBX-Att dataset and will serve as a solid baseline for future research.
• Score: 58.01014026139231
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Although deep learning algorithms have been intensively developed for computer-aided tuberculosis diagnosis (CTD), they mainly depend on carefully annotated datasets, leading to much time and resource consumption. Weakly supervised learning (WSL), which leverages coarse-grained labels to accomplish fine-grained tasks, has the potential to solve this problem. In this paper, we first propose a new large-scale tuberculosis (TB) chest X-ray dataset, namely the tuberculosis chest X-ray attribute dataset (TBX-Att), and then establish an attribute-assisted weakly-supervised framework to classify and localize TB by leveraging the attribute information to overcome the insufficiency of supervision in WSL scenarios. Specifically, first, the TBX-Att dataset contains 2000 X-ray images with seven kinds of attributes for TB relational reasoning, which are annotated by experienced radiologists. It also includes the public TBX11K dataset with 11200 X-ray images to facilitate weakly supervised detection. Second, we exploit a multi-scale feature interaction model for TB area classification and detection with attribute relational reasoning. The proposed model is evaluated on the TBX-Att dataset and will serve as a solid baseline for future research. The code and data will be available at https://github.com/GangmingZhao/tb-attribute-weak-localization.

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