CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 复杂系统研究
CONVOLUTIONAL NEURAL NETWORKS FOR PREDICTING MOLECULAR PROFILES OF NON-SMALL CELL LUNG CANCER
Dongdong,Yu1; Mu,Zhou2; Feng,Yang3; Di,Dong1; Olivier,Gevaert2; Zaiyi,Liu4; Jingyun,Shi5; Jie,Tian1
2017
Conference NameISBI2017
Source PublicationIEEE International Symposium on Biomedical Imaging. 2017.
Conference Date2017.04.17-2017.04.22
Conference Place澳大利亚墨尔本
AbstractQuantitative imaging biomarkers identification has become a powerful tool for predictive diagnosis given increasingly available clinical imaging data. In parallel, molecular profiles have been well documented in non-small cell lung cancers (NSCLCs). However, there has been limited studies on leveraging the two major sources for improving lung cancer computer-aided diagnosis. In this paper, we investigate the problem of predicting molecular profiles with CT imaging arrays in NSCLC. In particular, we formulate a discriminative convolutional neural network to learn deep features for predicting epidermal growth factor receptor (EGFR) mutation states that are associated with cancer cell growth. We evaluated our approach on two independent datasets including a discovery set with 595 patients (Datset1) and a validation set with 89 patients (Dataset2). Extensive experimental results demonstrated that the learned CNN-based features are effective in predicting EGFR mutation states (AUC=0.828, ACC=76.16%) on Dataset1, and it further demonstrated generalized predictive performance (AUC=0.668, ACC=67.55%) on Dataset2.
KeywordNon-small Cell Lung Carcinoma Convolutional Neural Networks Computed Tomography Computed-aided Diagnosis
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14468
Collection复杂系统管理与控制国家重点实验室_复杂系统研究
Corresponding AuthorJie,Tian
Affiliation1.The Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences
2.The Stanford Center for Biomedical Informatics Research, Stanford University
3.School of Computer and Information Technology, Beijing Jiaotong University
4.Department of Radiology, Guangdong Academy of Medical Sciences, Guangdong General Hospital
5.Department of Radiology, Shanghai Pulmonary Hospital, Tongji University School of Medicine
Recommended Citation
GB/T 7714
Dongdong,Yu,Mu,Zhou,Feng,Yang,et al. CONVOLUTIONAL NEURAL NETWORKS FOR PREDICTING MOLECULAR PROFILES OF NON-SMALL CELL LUNG CANCER[C],2017.
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