CASIA OpenIR  > 中国科学院分子影像重点实验室
A Multi-view Deep Convolutional Neural Networks for Lung Nodule Segmentation
Wang, Shuo1,3; Zhou, Mu2; Gevaert, Olivier2; Tang, Zhenchao4; Dong, Di1,3; Liu, Zhenyu1,3; Tian, Jie1,3
2017-07
Conference Name39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Conference Date2017-7
Conference PlaceJeju Island, Korea
Abstract

We present a multi-view convolutional neural
networks (MV-CNN) for lung nodule segmentation. The MVCNN
specialized in capturing a diverse set of nodule-sensitive
features from axial, coronal and sagittal views in CT images
simultaneously. The proposed network architecture consists of
three CNN branches, where each branch includes seven stacked
layers and takes multi-scale nodule patches as input. The three
CNN branches are then integrated with a fully connected layer
to predict whether the patch center voxel belongs to the nodule.
The proposed method has been evaluated on 893 nodules from
the public LIDC-IDRI dataset, where ground-truth annotations
and CT imaging data were provided. We showed that MV-CNN
demonstrated encouraging performance for segmenting various
type of nodules including juxta-pleural, cavitary, and nonsolid
nodules, achieving an average dice similarity coefficient
(DSC) of 77.67% and average surface distance (ASD) of 0.24,
outperforming conventional image segmentation approaches.

DOI10.1109/EMBC.2017.8037182
Indexed ByEI
Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/23574
Collection中国科学院分子影像重点实验室
Corresponding AuthorDong, Di; Liu, Zhenyu; Tian, Jie
Affiliation1.CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China
2.Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine, Stanford University, USA
3.University of Chinese Academy of Sciences, Beijing, China
4.School of Mechanical, Electrical & Information Engineering, Shandong University, Shandong, China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Wang, Shuo,Zhou, Mu,Gevaert, Olivier,et al. A Multi-view Deep Convolutional Neural Networks for Lung Nodule Segmentation[C],2017.
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