Accurate diagnosis of lung tissues for 2D Raman spectrogram by deep learning based on short-time Fourier transform.

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作者： Yafeng,Qi ^[1] ; Lin,Yang ^[2] ; Bangxu,Liu ^[1] ; Li,Liu ^[2] ; Yuhong,Liu ^[3] ; Qingfeng,Zheng ^[4] ; Dameng,Liu ^[5] ; Jianbin,Luo ^[1]

作者单位： State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China. ^[1] Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China. ^[2] State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China. Electronic address: liuyuhong@tsinghua.edu.cn. ^[3] Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China. Electronic address: qfzhengpku@163.com. ^[4] State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China. Electronic address: ldm@tsinghua.edu.cn. ^[5]

关键词 Deep learning Lung cancer Raman spectrogram Short-time Fourier transform

主题词傅里叶分析(Fourier Analysis);肺(Lung)

DOI 10.1016/j.aca.2021.338821

PMID 34535256

发布时间 2021-09-21

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Analytica chimica acta

2021年1179卷

338821页

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Accurate diagnosis of lung tissues for 2D Raman spectrogram by deep learning based on short-time Fourier transform.

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Accurate diagnosis of lung tissues for 2D Raman spectrogram by deep learning based on short-time Fourier transform.

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