Velocity extraction from spin-tagging MRI images using a weighted least-squares optical flow method

Stoitsis, J; Bastouni, E; Karampinos, DC; Bosshard, JC; Lu, J; Golemati, S; Wright, SM; Georgiadis, JG; Nikita, KS

dc.contributor.author	Stoitsis, J	en
dc.contributor.author	Bastouni, E	en
dc.contributor.author	Karampinos, DC	en
dc.contributor.author	Bosshard, JC	en
dc.contributor.author	Lu, J	en
dc.contributor.author	Golemati, S	en
dc.contributor.author	Wright, SM	en
dc.contributor.author	Georgiadis, JG	en
dc.contributor.author	Nikita, KS	en
dc.date.accessioned	2014-03-01T02:45:00Z
dc.date.available	2014-03-01T02:45:00Z
dc.date.issued	2007	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32087
dc.subject	Spin-tagging MRI	en
dc.subject	Velocity estimation	en
dc.subject	Weighted least-squares optical flow	en
dc.subject.other	Feature extraction	en
dc.subject.other	Image analysis	en
dc.subject.other	Least squares approximations	en
dc.subject.other	Measurement theory	en
dc.subject.other	Spin-tagging MRI	en
dc.subject.other	Velocity estimation	en
dc.subject.other	Weighted least-squares optical flow	en
dc.subject.other	Magnetic resonance imaging	en
dc.title	Velocity extraction from spin-tagging MRI images using a weighted least-squares optical flow method	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/IST.2007.379577	en
heal.identifier.secondary	http://dx.doi.org/10.1109/IST.2007.379577	en
heal.identifier.secondary	4258777	en
heal.publicationDate	2007	en
heal.abstract	Magnetic Resonance Imaging (MRI) can provide truly non-invasive measurements of internal flow fields. The extraction of velocity from spin-tagging images requires the quantitative tracking of grid nodes. A weighted least-squares optical flow method was used in this work to estimate the displacements of the grid nodes and tags from synthetic and real spin-tagging MRI images. To investigate the accuracy of the proposed method, synthetic spin-tagging images were generated using the Poiseuille law analytical profile. Three synthetic sequences with different levels of noise were generated and the average and maximum absolute errors were estimated for points corresponding to grid nodes and tags. Different sizes and shapes of region of interest (ROI) were investigated to determine the optimal size and shape for reliable extraction of velocity both for synthetic and real spin-tagging MRI images. The optimal ROI size was found to be 13×13 pixels2. The average and maximum absolute error for the velocity in vertical direction for synthetic data using the optimal ROI size ranged from 5.46% to 14.42% and from 6.39% to 31.96% respectively. © 2007 IEEE.	en
heal.journalName	Proceedings of the 2007 IEEE International Workshop on Imaging Systems and Techniques, IST'07	en
dc.identifier.doi	10.1109/IST.2007.379577	en