CASIA OpenIR  > 中国科学院分子影像重点实验室
Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation
Wang, Shuo1,3; Zhou, Mu2; Liu, Zaiyi4; Liu, Zhenyu1; Gu, Dongsheng1,3; Zang, Yali1,3; Dong, Di1,3; Gevaert, Olivier2; Tian, Jie1,3,5
Source PublicationMEDICAL IMAGE ANALYSIS
2017-08-01
Volume40Issue:40Pages:172-183
SubtypeArticle
AbstractAccurate lung nodule segmentation from computed tomography (CT) images is of great importance for image-driven lung cancer analysis. However, the heterogeneity of lung nodules and the presence of similar visual characteristics between nodules and their surroundings make it difficult for robust nodule segmentation. In this study, we propose a data-driven model, termed the Central Focused Convolutional Neural Networks (CF-CNN), to segment lung nodules from heterogeneous CT images. Our approach combines two key insights: 1) the proposed model captures a diverse set of nodule-sensitive features from both 3-D and 2-D CT images simultaneously; 2) when classifying an image voxel, the effects of its neighbor voxels can vary according to their spatial locations. We describe this phenomenon by proposing a novel central pooling layer retaining much information on voxel patch center, followed by a multi-scale patch learning strategy. Moreover, we design a weighted sampling to facilitate the model training, where training samples are selected according to their degree of segmentation difficulty. The proposed method has been extensively evaluated on the public LIDC dataset including 893 nodules and an independent dataset with 74 nodules from Guangdong General Hospital (GDGH). We showed that CF-CNN achieved superior segmentation performance with average dice scores of 82.15% and 80.02% for the two datasets respectively. Moreover, we compared our results with the inter-radiologists consistency on LIDC dataset, showing a difference in average dice score of only 1.98%. (C) 2017 Published by Elsevier B.V.
KeywordLung Nodule Segmentation Convolutional Neural Networks Deep Learning Computer-aided Diagnosis
WOS HeadingsScience & Technology ; Technology ; Life Sciences & Biomedicine
DOI10.1016/j.media.2017.06.014
WOS KeywordTHORACIC CT SCANS ; MR BRAIN IMAGES ; PULMONARY NODULES ; AUTOMATIC SEGMENTATION ; CONSORTIUM ; LESIONS
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(81227901 ; Science and Technology Service Network Initiative of the Chinese Academy of Sciences(KFJ-SW-STS-160) ; special program for science and technology development from the Ministry of science and technology, China(2017YFA0205200 ; National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health(R01EB020527) ; Instrument Developing Project of the Chinese Academy of Sciences(YZ201502) ; Beijing Municipal Science and Technology Commission([Z161100002616022) ; Youth Innovation Promotion Association CAS ; 61231004 ; 2017YFC1308701 ; 81501616 ; 2017YFC1309100 ; 81671851 ; 2016CZYD0001) ; 81527805 ; 81501549)
WOS Research AreaComputer Science ; Engineering ; Radiology, Nuclear Medicine & Medical Imaging
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications ; Engineering, Biomedical ; Radiology, Nuclear Medicine & Medical Imaging
WOS IDWOS:000407538000011
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/20306
Collection中国科学院分子影像重点实验室
Affiliation1.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
2.Stanford Univ, Dept Med, Stanford Ctr Biomed Informat Res BMIR, Stanford, CA 94305 USA
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.Guangdong Gen Hosp, Guangzhou 510080, Guangdong, Peoples R China
5.Beijing Key Lab Mol Imaging, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Wang, Shuo,Zhou, Mu,Liu, Zaiyi,et al. Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation[J]. MEDICAL IMAGE ANALYSIS,2017,40(40):172-183.
APA Wang, Shuo.,Zhou, Mu.,Liu, Zaiyi.,Liu, Zhenyu.,Gu, Dongsheng.,...&Tian, Jie.(2017).Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation.MEDICAL IMAGE ANALYSIS,40(40),172-183.
MLA Wang, Shuo,et al."Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation".MEDICAL IMAGE ANALYSIS 40.40(2017):172-183.
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