Detection of Solitary Pulmonary Nodules Based on Brain-Computer Interface

被引:13
|
作者
Qiu, Shi [1 ]
Li, Junjun [2 ]
Cong, Mengdi [3 ]
Wu, Chun [4 ]
Qin, Yan [4 ]
Liang, Ting [2 ,5 ]
机构
[1] Chinese Acad Sci, Xian Inst Opt & Precis Mech, Key Lab Spectral Imaging Technol CAS, Xian 710119, Peoples R China
[2] Xi An Jiao Tong Univ, Affiliated Hosp 1, Dept Radiol, Xian 710061, Peoples R China
[3] Childrens Hosp Hebei Prov, Dept Computed Tomog & Magnet Resonance, Shijiazhuang 050031, Peoples R China
[4] BeiJing Hitech Inst, Beijing 00085, Peoples R China
[5] Xi An Jiao Tong Univ, Sch Life Sci & Technol, Minist Educ, Dept Biomed Engn,Key Lab Biomed Informat Engn, Xian 710061, Peoples R China
基金
中国国家自然科学基金; 美国国家科学基金会;
关键词
IMAGE CLASSIFICATION; ALGORITHM;
D O I
10.1155/2020/4930972
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Solitary pulmonary nodules are the main manifestation of pulmonary lesions. Doctors often make diagnosis by observing the lung CT images. In order to further study the brain response structure and construct a brain-computer interface, we propose an isolated pulmonary nodule detection model based on a brain-computer interface. First, a single channel time-frequency feature extraction model is constructed based on the analysis of EEG data. Second, a multilayer fusion model is proposed to establish the brain-computer interface by connecting the brain electrical signal with a computer. Finally, according to image presentation, a three-frame image presentation method with different window widths and window positions is proposed to effectively detect the solitary pulmonary nodules.
引用
收藏
页数:10
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