DocumentCode :
523532
Title :
Automatic Detection of Pulmonary Nodules in Multi-slice CT Based on 3D Neural Networks with Adaptive Initial Weights
Author :
Wang, Qing-Zhu ; Wang, Ke ; Guo, Yang ; Wang, Xin-Zhu
Author_Institution :
Sch. of Commun. Eng., Jilin Univ., Changchun, China
Volume :
1
fYear :
2010
fDate :
11-12 May 2010
Firstpage :
833
Lastpage :
836
Abstract :
Detection of pulmonary nodules combined of extraction by multi-directions PCA and identification by 3D (three dimension) BP neural network is presented in the paper, which is different from most lung CAD algorithms, that it does not require any a priori information by human intervention but solely the information contained by the CT image itself, and it is capable to perform full automation which support the radiologists in their final decision. The technique is tested against 60 cases of different pulmonary nodules which are screened out by cancer experts. Results confirm the validity of technique as well as enhanced performance.
Keywords :
backpropagation; computerised tomography; medical image processing; neural nets; principal component analysis; 3D neural networks; adaptive initial weights; backpropagation; computerised tomography; multidirections PCA; multislice ct; principal component analysis; pulmonary nodules detection; Adaptive systems; Automation; Cancer; Computed tomography; Data mining; Humans; Lungs; Neural networks; Principal component analysis; Testing; 3D neural network; CT images; component; multi-directions PCA;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-7279-6
Electronic_ISBN :
978-1-4244-7280-2
Type :
conf
DOI :
10.1109/ICICTA.2010.751
Filename :
5522557
Link To Document :
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