• 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