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Nonlinear elasticity imaging using u...

Erkamp, Ramon Quido.

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Nonlinear elasticity imaging using ultrasound.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Nonlinear elasticity imaging using ultrasound./
作者:	Erkamp, Ramon Quido.
面頁冊數:	123 p.
附註:	Source: Dissertation Abstracts International, Volume: 64-09, Section: B, page: 4484.
Contained By:	Dissertation Abstracts International64-09B.
標題:	Engineering, Biomedical. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3106055

Nonlinear elasticity imaging using ultrasound.
Erkamp, Ramon Quido.

Nonlinear elasticity imaging using ultrasound. - 123 p.

Source: Dissertation Abstracts International, Volume: 64-09, Section: B, page: 4484.

Thesis (Ph.D.)--University of Michigan, 2003.

Currently, elasticity imaging procedures assume that the elastic modulus does not change with deformation. Most biological tissues, however, exhibit strain hardening. This nonlinear behavior makes contrast in elasticity images strain dependent, and for soft tissue generally results in sub-optimal elastic contrast. This work seeks to exploit strain hardening, using it as a mechanism to improve image contrast.Subjects--Topical Terms:

1017684
Engineering, Biomedical.

Nonlinear elasticity imaging using ultrasound.
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100 1 $a Erkamp, Ramon Quido. $3 1951959
245 1 0 $a Nonlinear elasticity imaging using ultrasound.
300 $a 123 p.
500 $a Source: Dissertation Abstracts International, Volume: 64-09, Section: B, page: 4484.
500 $a Chair: Matthew O'Donnell.
502 $a Thesis (Ph.D.)--University of Michigan, 2003.
520 $a Currently, elasticity imaging procedures assume that the elastic modulus does not change with deformation. Most biological tissues, however, exhibit strain hardening. This nonlinear behavior makes contrast in elasticity images strain dependent, and for soft tissue generally results in sub-optimal elastic contrast. This work seeks to exploit strain hardening, using it as a mechanism to improve image contrast.
520 $a Direct mechanical measurement procedures for characterizing the nonlinear elastic behavior of tissue and phantom materials are developed. Based on measured phantom material behavior a nonlinear finite element simulation of a phantom experiment is performed, and a sequence of synthetic RF ultrasound frames generated. The data form a 3-D set with depth, lateral, and preload dimensions. Speckle tracking is used to find interframe displacements, and registration techniques bring all data to the geometry of the first frame. Data are fit to a 3-D second order polynomial for each pixel that adjusts for deformation irregularities. Reconstructed frame-to-frame strain images using this model can result in improved contrast to noise ratios (CNR), without any sacrifice in spatial resolution. The same model allows extraction of relative hardening at all preload levels; it represents the rate of change of strain as a function of applied phantom preload and is an independent contrast mechanism. Mathematical simplifications lead to an implementation requiring little computation.
520 $a As the real underlying displacements of the synthetic RF data are know, exact CNR calculations are performed to evaluate performance. For reconstructed frame-to-frame strain images the CNR improved by more than a factor of 2 over the entire range of preload levels (0--11%), compared to their raw frame-to-frame counterparts. Maximum CNR is at 0.2% and 10.6% preload. The best-case relative hardening image is at preload 5.13%. Its CNR of 8.03 is a nearly fourfold improvement over the reconstructed frame-to-frame strain image at that preload (9 times better than raw strain). At all but the highest preload level, relative hardening outperforms reconstructed frame-to-frame strains. Best case relative hardening beats best case reconstructed strain by a factor 1.5 and best case raw strain by a factor of 3.6. Finally, the same algorithm is also used for a real phantom experiment.
590 $a School code: 0127.
650 4 $a Engineering, Biomedical. $3 1017684
650 4 $a Health Sciences, Radiology. $3 1019076
650 4 $a Engineering, Mechanical. $3 783786
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710 2 0 $a University of Michigan. $3 777416
773 0 $t Dissertation Abstracts International $g 64-09B.
790 1 0 $a O'Donnell, Matthew, $e advisor
790 $a 0127
791 $a Ph.D.
792 $a 2003
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3106055