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

John Stoitsis; Effi Bastouni; Dimitrios C. Karampinos; John C. Bosshard; Jiaxi Lu; Spyretta Golemati; Steven M. Wright; John G. Georgiadis; Konstantina S. Nikita

doi:10.1109/ist.2007.379577

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

John Stoitsis, Effi Bastouni, Dimitrios C. Karampinos, John C. Bosshard, Jiaxi Lu, Spyretta Golemati, Steven M. Wright, John G. Georgiadis, Konstantina S. Nikita

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

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.

Original language	English
Title of host publication	Proceedings of the 2007 IEEE International Workshop on Imaging Systems and Techniques, IST'07
Publisher	IEEE Computer Society
ISBN (Print)	1424409659, 9781424409655
DOIs	https://doi.org/10.1109/ist.2007.379577
State	Published - 2007
Externally published	Yes
Event	2007 IEEE International Workshop on Imaging Systems and Techniques, IST'07 - Cracovia, Poland Duration: 4 May 2007 → 5 May 2007

Publication series

Name	Proceedings of the 2007 IEEE International Workshop on Imaging Systems and Techniques, IST'07

Conference

Conference	2007 IEEE International Workshop on Imaging Systems and Techniques, IST'07
Country/Territory	Poland
City	Cracovia
Period	4/05/07 → 5/05/07

Keywords

Spin-tagging MRI
Velocity estimation
Weighted least-squares optical flow

Access to Document

10.1109/ist.2007.379577

Cite this

Stoitsis, J., Bastouni, E., Karampinos, D. C., Bosshard, J. C., Lu, J., Golemati, S., Wright, S. M., Georgiadis, J. G., & Nikita, K. S. (2007). Velocity extraction from spin-tagging MRI images using a weighted least-squares optical flow method. In Proceedings of the 2007 IEEE International Workshop on Imaging Systems and Techniques, IST'07 Article 4258777 (Proceedings of the 2007 IEEE International Workshop on Imaging Systems and Techniques, IST'07). IEEE Computer Society. https://doi.org/10.1109/ist.2007.379577

Stoitsis, John ; Bastouni, Effi ; Karampinos, Dimitrios C. et al. / Velocity extraction from spin-tagging MRI images using a weighted least-squares optical flow method. Proceedings of the 2007 IEEE International Workshop on Imaging Systems and Techniques, IST'07. IEEE Computer Society, 2007. (Proceedings of the 2007 IEEE International Workshop on Imaging Systems and Techniques, IST'07).

@inproceedings{8d63b34671074f7c81bf50f925262daa,

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

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.",

keywords = "Spin-tagging MRI, Velocity estimation, Weighted least-squares optical flow",

author = "John Stoitsis and Effi Bastouni and Karampinos, {Dimitrios C.} and Bosshard, {John C.} and Jiaxi Lu and Spyretta Golemati and Wright, {Steven M.} and Georgiadis, {John G.} and Nikita, {Konstantina S.}",

year = "2007",

doi = "10.1109/ist.2007.379577",

language = "English",

isbn = "1424409659",

series = "Proceedings of the 2007 IEEE International Workshop on Imaging Systems and Techniques, IST'07",

publisher = "IEEE Computer Society",

booktitle = "Proceedings of the 2007 IEEE International Workshop on Imaging Systems and Techniques, IST'07",

note = "2007 IEEE International Workshop on Imaging Systems and Techniques, IST'07 ; Conference date: 04-05-2007 Through 05-05-2007",

}

Stoitsis, J, Bastouni, E, Karampinos, DC, Bosshard, JC, Lu, J, Golemati, S, Wright, SM, Georgiadis, JG & Nikita, KS 2007, Velocity extraction from spin-tagging MRI images using a weighted least-squares optical flow method. in Proceedings of the 2007 IEEE International Workshop on Imaging Systems and Techniques, IST'07., 4258777, Proceedings of the 2007 IEEE International Workshop on Imaging Systems and Techniques, IST'07, IEEE Computer Society, 2007 IEEE International Workshop on Imaging Systems and Techniques, IST'07, Cracovia, Poland, 4/05/07. https://doi.org/10.1109/ist.2007.379577

Velocity extraction from spin-tagging MRI images using a weighted least-squares optical flow method. / Stoitsis, John; Bastouni, Effi; Karampinos, Dimitrios C. et al.
Proceedings of the 2007 IEEE International Workshop on Imaging Systems and Techniques, IST'07. IEEE Computer Society, 2007. 4258777 (Proceedings of the 2007 IEEE International Workshop on Imaging Systems and Techniques, IST'07).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Velocity extraction from spin-tagging MRI images using a weighted least-squares optical flow method

AU - Stoitsis, John

AU - Bastouni, Effi

AU - Karampinos, Dimitrios C.

AU - Bosshard, John C.

AU - Lu, Jiaxi

AU - Golemati, Spyretta

AU - Wright, Steven M.

AU - Georgiadis, John G.

AU - Nikita, Konstantina S.

PY - 2007

Y1 - 2007

N2 - 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.

AB - 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.

KW - Spin-tagging MRI

KW - Velocity estimation

KW - Weighted least-squares optical flow

UR - http://www.scopus.com/inward/record.url?scp=34748822517&partnerID=8YFLogxK

U2 - 10.1109/ist.2007.379577

DO - 10.1109/ist.2007.379577

M3 - Conference contribution

AN - SCOPUS:34748822517

SN - 1424409659

SN - 9781424409655

T3 - Proceedings of the 2007 IEEE International Workshop on Imaging Systems and Techniques, IST'07

BT - Proceedings of the 2007 IEEE International Workshop on Imaging Systems and Techniques, IST'07

PB - IEEE Computer Society

T2 - 2007 IEEE International Workshop on Imaging Systems and Techniques, IST'07

Y2 - 4 May 2007 through 5 May 2007

ER -

Stoitsis J, Bastouni E, Karampinos DC, Bosshard JC, Lu J, Golemati S et al. Velocity extraction from spin-tagging MRI images using a weighted least-squares optical flow method. In Proceedings of the 2007 IEEE International Workshop on Imaging Systems and Techniques, IST'07. IEEE Computer Society. 2007. 4258777. (Proceedings of the 2007 IEEE International Workshop on Imaging Systems and Techniques, IST'07). doi: 10.1109/ist.2007.379577

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

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this