• DocumentCode
    2048054
  • Title

    An Optimization Algorithm to Inverse Problem in 2-D Optical Computed Tomography by BP Neural Network

  • Author

    Wu, Qiong ; Qian, Zhiyu ; Gu, Yueqing

  • Author_Institution
    Dept. of Biomed. Eng., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing
  • fYear
    2006
  • fDate
    16-18 Oct. 2006
  • Firstpage
    163
  • Lastpage
    166
  • Abstract
    An optimization approach is introduced to inverse model of optical CT, which can reconstruct the optical properties namely scattering coefficients of thick tissue such as brain and breast tissues. A modeling and simulation tool named FEMLAB and based on finite element method has been tested wherein the forward models based on the diffusion equation. Solve the inverse model as an optimization approach, including the optimization methods of optical properties. An improved BP neural network which based on Levenberg-Marquardt optimization algorithm was employed to solve this inverse problem. The simulation results show that the algorithm can reconstruct the optical image quickly and accurately.
  • Keywords
    backpropagation; bio-optics; biological tissues; biomedical optical imaging; computerised tomography; finite element analysis; image reconstruction; inverse problems; light scattering; medical image processing; neural nets; optical tomography; 2D optical computed tomography; BP neural network; FEMLAB; Levenberg-Marquardt optimization algorithm; brain tissues; breast tissues; diffusion equation; finite element method; inverse problem; optical CT reconstruction; optical properties; optimization algorithm; scattering coefficients; Biological neural networks; Brain modeling; Computed tomography; Image reconstruction; Inverse problems; Neural networks; Optical computing; Optical fiber networks; Optical scattering; Optimization methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biophotonics, Nanophotonics and Metamaterials, 2006. Metamaterials 2006. International Symposium on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    0-7803-9773-8
  • Electronic_ISBN
    0-7803-9774-6
  • Type

    conf

  • DOI
    10.1109/METAMAT.2006.335025
  • Filename
    4134764