A Pulmonary Nodule Spiculation Recognition Algorithm Based on Generative Adversarial Networks | |
Zhang, Jing1; Qiu, Shi2; Cui, Xiaohai1; Liang, Ting3,4 | |
作者部门 | 光谱成像技术研究室 |
2022-06-24 | |
发表期刊 | BIOMED RESEARCH INTERNATIONAL |
ISSN | 2314-6133;2314-6141 |
卷号 | 2022 |
产权排序 | 2 |
摘要 | Pulmonary nodules have been found as the main pathological change in the lung. Signs of pulmonary nodule lay the major basis for the recognition of the benign and malignant of pulmonary nodules. The spiculation of pulmonary nodules is one of the main signs. Pulmonary nodules are small in volume, so they are difficult to extract accurately. Moreover, the number of spiculation samples is limited, so it is difficult to build a stable network structure. Thus, a novel pulmonary nodule spiculation recognition algorithm is proposed. MCA (morphological component analysis) model is built to segment pulmonary nodules in accordance with the composition of pulmonary CT images. Subsequently, the maximum density projection mechanism is introduced to characterize the boundary features of pulmonary nodules to the maximum extent. Inspired by time series dynamic programming, this paper proposes DTW (dynamic time warping) distance to measure data similarity. Lastly, a semisupervised generative adversarial network is built to solve the problem of insufficient positive samples, and it is capable of recognizing pulmonary nodule spiculation. As revealed by the experimental result, the proposed algorithm exhibited strong robustness. |
DOI | 10.1155/2022/3341924 |
收录类别 | SCI |
语种 | 英语 |
WOS记录号 | WOS:000867779500002 |
出版者 | HINDAWI LTD |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.opt.ac.cn/handle/181661/96196 |
专题 | 光谱成像技术研究室 |
通讯作者 | Liang, Ting |
作者单位 | 1.Xi An Jiao Tong Univ, Dept Thorac Surg, Affiliated Hosp 1, Xian, Shaanxi, Peoples R China 2.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Key Lab Spectral Imaging Technol CAS, Xian, Peoples R China 3.Xi An Jiao Tong Univ, Dept Radiol, Affiliated Hosp 1, Xian, Peoples R China 4.Xi An Jiao Tong Univ, Sch Life Sci & Technol, Dept Biomed Engn, Key Lab Biomed Informat Engn,Minist Educ, Xian, Peoples R China |
推荐引用方式 GB/T 7714 | Zhang, Jing,Qiu, Shi,Cui, Xiaohai,et al. A Pulmonary Nodule Spiculation Recognition Algorithm Based on Generative Adversarial Networks[J]. BIOMED RESEARCH INTERNATIONAL,2022,2022. |
APA | Zhang, Jing,Qiu, Shi,Cui, Xiaohai,&Liang, Ting.(2022).A Pulmonary Nodule Spiculation Recognition Algorithm Based on Generative Adversarial Networks.BIOMED RESEARCH INTERNATIONAL,2022. |
MLA | Zhang, Jing,et al."A Pulmonary Nodule Spiculation Recognition Algorithm Based on Generative Adversarial Networks".BIOMED RESEARCH INTERNATIONAL 2022(2022). |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
A Pulmonary Nodule S(1687KB) | 期刊论文 | 出版稿 | 限制开放 | CC BY-NC-SA | 请求全文 |
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