摘要
With the increasing number of lung cancer patients, the CAD system is playing an increasingly important rule in the field of automatic identification for medical images. Since the 3D characteristics of low-dose CT images make the 3D convolution more suitable than 2D convolution, in this paper, we propose a method to detect lung nodule of lung CT images using 3D convolutional neural networks. Combined with the traditional morphological preprocessing methods, 3D convolutional neural networks are applied to lung CT images. The experimental accuracy indicates that this method is suitable for the problem of lung nodule detection and has great room to improve. The experimental results also demonstrate that the application of deep learning in the medical field will bring great progress for medical development.
| 源语言 | 英语 |
|---|---|
| 主期刊名 | Conference Proceedings - 2017 International Conference on the Frontiers and Advances in Data Science, FADS 2017 |
| 出版商 | Institute of Electrical and Electronics Engineers Inc. |
| 页 | 7-10 |
| 页数 | 4 |
| ISBN(电子版) | 9781538631485 |
| DOI | |
| 出版状态 | 已出版 - 1 7月 2017 |
| 活动 | 2017 International Conference on the Frontiers and Advances in Data Science, FADS 2017 - Xian, 中国 期限: 23 10月 2017 → 25 10月 2017 |
出版系列
| 姓名 | Conference Proceedings - 2017 International Conference on the Frontiers and Advances in Data Science, FADS 2017 |
|---|---|
| 卷 | 2018-January |
会议
| 会议 | 2017 International Conference on the Frontiers and Advances in Data Science, FADS 2017 |
|---|---|
| 国家/地区 | 中国 |
| 市 | Xian |
| 时期 | 23/10/17 → 25/10/17 |
联合国可持续发展目标
此成果有助于实现下列可持续发展目标:
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可持续发展目标 3 良好健康与福祉
学术指纹
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