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https://dspace.ctu.edu.vn/jspui/handle/123456789/109539
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DC Field | Value | Language |
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dc.contributor.author | Nguyen, Chi Cuong | - |
dc.contributor.author | Nguyen, Long Giang | - |
dc.contributor.author | Tran, Giang Son | - |
dc.date.accessioned | 2024-12-23T12:14:57Z | - |
dc.date.available | 2024-12-23T12:14:57Z | - |
dc.date.issued | 2022 | - |
dc.identifier.issn | 1813-9663 | - |
dc.identifier.uri | https://dspace.ctu.edu.vn/jspui/handle/123456789/109539 | - |
dc.description.abstract | Lung cancer is one of the most serious cancer-related diseases in Vietnam and all over the world. Early detection of lung nodules can help to increase the survival rate of lung cancer patients. Computer-aided diagnosis (CAD) systems are proposed in the literature for early detection of lung nodules. However, most of the current CAD systems are based on the building of high-quality machine learning models for a fixed dataset rather than taking into account the dataset properties which are very important for the lung cancer diagnosis. In this paper, we follow the direction of data-centric approach for lung nodule detection by proposing a data-centric method to improve detection performance of lung nodules on CT scans. Our method takes into account the dataset-specific features (nodule sizes and aspect ratios) to train detection models as well as add more training data from local Vietnamese hospital. We experiment our method on the three widely used object detection networks (Faster R-CNN, YOLOv3 and RetinaNet). The experimental results show that our proposed method improves detection sensitivity of these object detection models up to 4.24%. | vi_VN |
dc.language.iso | en | vi_VN |
dc.relation.ispartofseries | Journal of Computer Science and Cybernetics;Vol.38, No.03 .- P.229-243 | - |
dc.subject | Data-centric learning | vi_VN |
dc.subject | Deep learning | vi_VN |
dc.subject | Pulmonary nodule detection | vi_VN |
dc.title | A data-centric deep learning method for pulmonary nodule detection | vi_VN |
dc.type | Article | vi_VN |
Appears in Collections: | Tin học và Điều khiển học (Journal of Computer Science and Cybernetics) |
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_file_ Restricted Access | 6.14 MB | Adobe PDF | ||
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