• DocumentCode
    2805988
  • Title

    Exploiting MR venography segmentation for the accurate model estimation of BOLD signal

  • Author

    Hu, Zhenghui ; Fang, Xin ; Shen, Xiaoyan ; Shi, Pengcheng

  • Author_Institution
    Dept. of Opt. Eng., Zhejiang Univ., Hangzhou, China
  • fYear
    2009
  • fDate
    June 28 2009-July 1 2009
  • Firstpage
    706
  • Lastpage
    709
  • Abstract
    The amplitude of the BOLD signal depends heavily upon the resting blood volume fraction (V0). However, most existing haemodynamic data assimilation studies pretermit such concern through assigning arbitrarily the value in a physiological plausible range. In this work, we presented the first exploration of the influence of the fraction V0 to model estimation, where the exact value of V0 was calibrated by MR angiography experiment. Our results show this process may greatly increase the accuracy of the data assimilation procedure. Furthermore, they also suggest that the result of traditional intensity-based activation inference would displace spatially from the realistic activated locus, the estimated neuronal efficiency parameter epsiv can accurately label the activated region, thus is a better candidate to evaluate activation level.
  • Keywords
    biomedical MRI; blood vessels; brain; haemodynamics; image segmentation; medical image processing; neurophysiology; MR angiography; MR imaging; blood volume fraction; bold signal model estimation; cerebral blood flow; intensity-based activation inference; neuronal efficiency parameter; venography segmentation; Angiography; Blood flow; Brain modeling; Data assimilation; Educational institutions; Nonlinear optics; Optical computing; Optical sensors; Parameter estimation; Veins; angiography; haemodynamic data assimilation; neuronal efficiency parameter ε; the resting blood volume fraction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on
  • Conference_Location
    Boston, MA
  • ISSN
    1945-7928
  • Print_ISBN
    978-1-4244-3931-7
  • Electronic_ISBN
    1945-7928
  • Type

    conf

  • DOI
    10.1109/ISBI.2009.5193145
  • Filename
    5193145