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Noise and error propagation in diffu...

Desai, Shital Bipin.

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Noise and error propagation in diffusion tensor imaging.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Noise and error propagation in diffusion tensor imaging./
Author:	Desai, Shital Bipin.
Description:	85 p.
Notes:	Source: Masters Abstracts International, Volume: 43-06, page: 2333.
Contained By:	Masters Abstracts International43-06.
Subject:	Engineering, Electronics and Electrical. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1426580
ISBN:	9780542103735

Noise and error propagation in diffusion tensor imaging.
Desai, Shital Bipin.

Noise and error propagation in diffusion tensor imaging. - 85 p.

Source: Masters Abstracts International, Volume: 43-06, page: 2333.

Thesis (M.S.E.E.)--West Virginia University, 2005.

Diffusion Tensor Imaging (DTI) is the in vivo visualization and analysis of white matter fiber tracts by measuring the anisotropy of water molecule diffusion in the brain tissue. DTI has been increasingly used in clinical imaging. Diffusion weighted images are affected by noise from the human subject and the MRI scanner. This thesis studies the error propagation in the calculation of the DTI invariant anisotropy, mainly the Fractional Anisotropy (FA) using four methods and their comparison in terms of error, filtering and computational efficiency using simulated and human brain data. These methods were Diffusion Tensor, Diffusion Ellipsoid, Hasan and Platonic Variance. The results showed similar trends across the simulated and real data sets. Of the four methods used to calculate FA, the Hasan method without diffusion tensor yielded best computational efficiency, but poor noise robustness, whereas the Platonic Variance method was more robust to noise and provided good computational efficiency.

ISBN: 9780542103735Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

Noise and error propagation in diffusion tensor imaging.
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020 $a 9780542103735
035 $a (UnM)AAI1426580
035 $a AAI1426580
040 $a UnM $c UnM
100 1 $a Desai, Shital Bipin. $3 1913105
245 1 0 $a Noise and error propagation in diffusion tensor imaging.
300 $a 85 p.
500 $a Source: Masters Abstracts International, Volume: 43-06, page: 2333.
500 $a Chair: Donald Adjeroh.
502 $a Thesis (M.S.E.E.)--West Virginia University, 2005.
520 $a Diffusion Tensor Imaging (DTI) is the in vivo visualization and analysis of white matter fiber tracts by measuring the anisotropy of water molecule diffusion in the brain tissue. DTI has been increasingly used in clinical imaging. Diffusion weighted images are affected by noise from the human subject and the MRI scanner. This thesis studies the error propagation in the calculation of the DTI invariant anisotropy, mainly the Fractional Anisotropy (FA) using four methods and their comparison in terms of error, filtering and computational efficiency using simulated and human brain data. These methods were Diffusion Tensor, Diffusion Ellipsoid, Hasan and Platonic Variance. The results showed similar trends across the simulated and real data sets. Of the four methods used to calculate FA, the Hasan method without diffusion tensor yielded best computational efficiency, but poor noise robustness, whereas the Platonic Variance method was more robust to noise and provided good computational efficiency.
590 $a School code: 0256.
650 4 $a Engineering, Electronics and Electrical. $3 626636
650 4 $a Health Sciences, Radiology. $3 1019076
690 $a 0544
690 $a 0574
710 2 0 $a West Virginia University. $3 1017532
773 0 $t Masters Abstracts International $g 43-06.
790 1 0 $a Adjeroh, Donald, $e advisor
790 $a 0256
791 $a M.S.E.E.
792 $a 2005
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1426580