Journal article
A dataset of pulmonary lesions with Multiple-Level attributes and fine contours
Frontiers in Digital Health, Vol.2, Art. 609349
2021
Abstract
Lung cancer is a life-threatening disease and its diagnosis is of great significance. Data scarcity and unavailability of datasets is a major bottleneck in lung cancer research. In this paper, we introduce a dataset of pulmonary lesions for designing the computer-aided diagnosis (CAD) systems. The dataset has fine contour annotations and nine attribute annotations. We define the structure of the dataset in detail, and then discuss the relationship of the attributes and pathology, and the correlation between the nine attributes with the chi-square test. To demonstrate the contribution of our dataset to computer-aided system design, we define four tasks that can be developed using our dataset. Then, we use our dataset to model multi-attribute classification tasks. We discuss the performance in 2D, 2.5D, and 3D input modes of the classification model. To improve performance, we introduce two attention mechanisms and verify the principles of the attention mechanisms through visualization. Experimental results show the relationship between different models and different levels of attributes.
Details
- Title
- A dataset of pulmonary lesions with Multiple-Level attributes and fine contours
- Authors/Creators
- P. Li (Author/Creator) - Shanghai Blood CenterX. Kong (Author/Creator) - Xidian UniversityJ. Li (Author/Creator) - Xidian UniversityG. Zhu (Author/Creator) - Xidian UniversityX. Lu (Author/Creator) - Shanghai Blood CenterP. Shen (Author/Creator) - Shanghai Blood CenterS.A.A. Shah (Author/Creator) - Murdoch UniversityM. Bennamoun (Author/Creator) - The University of Western AustraliaT. Hua (Author/Creator) - Huashan Hospital
- Publication Details
- Frontiers in Digital Health, Vol.2, Art. 609349
- Publisher
- Frontiers Media
- Identifiers
- 991005540426207891
- Copyright
- © 2021 The Authors.
- Murdoch Affiliation
- College of Science, Health, Engineering and Education
- Language
- English
- Resource Type
- Journal article
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