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Exponential Signal Decay Models for ...

Yin, Xiaoming.

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Exponential Signal Decay Models for Quantitative Gradient Echo Magnetic Resonance Imaging.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Exponential Signal Decay Models for Quantitative Gradient Echo Magnetic Resonance Imaging./
作者:	Yin, Xiaoming.
面頁冊數:	117 p.
附註:	Source: Dissertation Abstracts International, Volume: 72-08, Section: B, page: .
Contained By:	Dissertation Abstracts International72-08B.
標題:	Engineering, Electronics and Electrical. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3456722
ISBN:	9781124663111

Exponential Signal Decay Models for Quantitative Gradient Echo Magnetic Resonance Imaging.
Yin, Xiaoming.

Exponential Signal Decay Models for Quantitative Gradient Echo Magnetic Resonance Imaging. - 117 p.

Source: Dissertation Abstracts International, Volume: 72-08, Section: B, page: .

Thesis (Ph.D.)--Northwestern University, 2011.

Magnetic resonance imaging (MRI) is non-harmful, flexible, and powerful in revealing anatomy. Each voxel value within an MR image is dependent upon multiple intrinsic values. This work investigated two aspects of the intrinsic values provided by gradient echo (GRE) imaging: spin-spin relaxation time and chemical shift differences.

ISBN: 9781124663111Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

Exponential Signal Decay Models for Quantitative Gradient Echo Magnetic Resonance Imaging.
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245 1 0 $a Exponential Signal Decay Models for Quantitative Gradient Echo Magnetic Resonance Imaging.
300 $a 117 p.
500 $a Source: Dissertation Abstracts International, Volume: 72-08, Section: B, page: .
500 $a Advisers: Aggelos K. Katsaggelos; Andrew C. Larson.
502 $a Thesis (Ph.D.)--Northwestern University, 2011.
520 $a Magnetic resonance imaging (MRI) is non-harmful, flexible, and powerful in revealing anatomy. Each voxel value within an MR image is dependent upon multiple intrinsic values. This work investigated two aspects of the intrinsic values provided by gradient echo (GRE) imaging: spin-spin relaxation time and chemical shift differences.
520 $a Spin-spin relaxation time, or T2*, is unique for different tissue types and has been used on many abdominal imaging applications. Conventionally, R2* maps are derived via mono-exponential fitting of signal decay within a series of gradient echo (GRE) images reconstructed from multi-channel datasets combined using a root sum-of-squares (RSS) approach. However, the noise bias at low SNR TEs from RSS reconstructed data often causes underestimation of R2* values. In phantom, ex vivo animal model, and normal volunteer studies, we investigated the accuracy of low SNR R2* measurement when combining truncation and coil combination methods. The accuracy for R2* estimations was shown to be affected by the intrinsic R2* value, SNR level, and chosen reconstruction method. R2* estimation error was found to decrease with increasing SNR level, decreasing R2* value, and use of the optimal B1-weighted combined (OBC) image reconstruction method. Data truncation based upon rigorous voxel-wise SNR estimates can reduce R2* measurement error in the setting of low SNR with fast signal decay. When optimal SNR truncation thresholds are unknown, the OBC method can provide optimal R2* measurements given the minimal truncation requirements.
520 $a The chemical shift between water and fat nuclei results a bi-exponential signal model signal under GRE imaging. Each voxel could contain an unknown amount of decaying water and decaying fat. Using variable projection (VARPRO) method, this work not only investigated into accurate fat-water quantification but also extended fatwater decomposition into a widely accepted palliative therapy for the treatment of unresectable hepatocellular carcinoma, transcatheter arterial chemoembolization (TACE). Through a healthy rat model, we were able to provide "angiograms" for lipiodol delivery through portal vein and also conducted quantitative estimation of lipiodol concentration following transcatheter delivery to liver tissues.
590 $a School code: 0163.
650 4 $a Engineering, Electronics and Electrical. $3 626636
650 4 $a Health Sciences, Radiology. $3 1019076
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690 $a 0574
710 2 $a Northwestern University. $b Electrical and Computer Engineering. $3 1022291
773 0 $t Dissertation Abstracts International $g 72-08B.
790 1 0 $a Katsaggelos, Aggelos K., $e advisor
790 1 0 $a Larson, Andrew C., $e advisor
790 1 0 $a Sahakian, Alan $e committee member
790 $a 0163
791 $a Ph.D.
792 $a 2011
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3456722