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
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