A multi-feature image retrieval scheme for pulmonary nodule diagnosis Article Swipe
YOU?
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· 2020
· Open Access
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· DOI: https://doi.org/10.1097/md.0000000000018724
Deep analysis of radiographic images can quantify the extent of intra-tumoral heterogeneity for personalized medicine. In this paper, we propose a novel content-based multi-feature image retrieval (CBMFIR) scheme to discriminate pulmonary nodules benign or malignant. Two types of features are applied to represent the pulmonary nodules. With each type of features, a single-feature distance metric model is proposed to measure the similarity of pulmonary nodules. And then, multiple single-feature distance metric models learned from different types of features are combined to a multi-feature distance metric model. Finally, the learned multi-feature distance metric is used to construct a content-based image retrieval (CBIR) scheme to assist the doctors in diagnosis of pulmonary nodules. The classification accuracy and retrieval accuracy are used to evaluate the performance of the scheme. The classification accuracy is 0.955 ± 0.010, and the retrieval accuracies outperform the comparison methods. The proposed CBMFIR scheme is effective in diagnosis of pulmonary nodules. Our method can better integrate multiple types of features from pulmonary nodules.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1097/md.0000000000018724
- OA Status
- gold
- Cited By
- 11
- References
- 27
- Related Works
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- OpenAlex ID
- https://openalex.org/W3002330560
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3002330560Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1097/md.0000000000018724Digital Object Identifier
- Title
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A multi-feature image retrieval scheme for pulmonary nodule diagnosisWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
- Publication date
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2020-01-01Full publication date if available
- Authors
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Guohui Wei, Min Qiu, Kuixing Zhang, Ming Li, Dejian Wei, Yanjun Li, Peiyu Liu, Hui Cao, Mengmeng Xing, Feng YangList of authors in order
- Landing page
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https://doi.org/10.1097/md.0000000000018724Publisher landing page
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1097/md.0000000000018724Direct OA link when available
- Concepts
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Feature (linguistics), Metric (unit), Pattern recognition (psychology), Artificial intelligence, Medicine, Image retrieval, Similarity (geometry), Scheme (mathematics), Image (mathematics), Computer science, Mathematics, Mathematical analysis, Operations management, Linguistics, Philosophy, EconomicsTop concepts (fields/topics) attached by OpenAlex
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11Total citation count in OpenAlex
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2025: 3, 2024: 2, 2023: 1, 2022: 3, 2021: 1Per-year citation counts (last 5 years)
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27Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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