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Stochastic signal processing methods...

Ingle, Atul.

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Stochastic signal processing methods for shear wave imaging using ultrasound.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Stochastic signal processing methods for shear wave imaging using ultrasound./
Author:	Ingle, Atul.
Description:	196 p.
Notes:	Source: Dissertation Abstracts International, Volume: 77-01(E), Section: B.
Contained By:	Dissertation Abstracts International77-01B(E).
Subject:	Electrical engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3721821
ISBN:	9781339035963

Stochastic signal processing methods for shear wave imaging using ultrasound.
Ingle, Atul.

Stochastic signal processing methods for shear wave imaging using ultrasound. - 196 p.

Source: Dissertation Abstracts International, Volume: 77-01(E), Section: B.

Thesis (Ph.D.)--The University of Wisconsin - Madison, 2015.

Hepatocellular carcinoma is one of the leading causes of cancer related deaths worldwide. Percutaneous needle-based tumor ablation is a minimally invasive treatment method for liver tumors in patients that are not candidates for surgery. In order to prevent recurrence, it is crucial that the right volume of tissue and a safety margin around the tumor are completely ablated during treatment. Although magnetic resonance imaging and computed X-ray tomography are currently used for monitoring the procedure, ultrasound imaging is potentially safer and more cost-effective and can also provide real-time high frame rate imaging capabilities. Information about tissue stiffness obtained using ultrasound elastography can play an important role in locating the boundary of ablated tissue and help in planning and execution of the ablation procedure.

ISBN: 9781339035963Subjects--Topical Terms:

649834
Electrical engineering.

Stochastic signal processing methods for shear wave imaging using ultrasound.
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020 $a 9781339035963
035 $a (MiAaPQ)AAI3721821
035 $a AAI3721821
040 $a MiAaPQ $c MiAaPQ
100 1 $a Ingle, Atul. $3 3184256
245 1 0 $a Stochastic signal processing methods for shear wave imaging using ultrasound.
300 $a 196 p.
500 $a Source: Dissertation Abstracts International, Volume: 77-01(E), Section: B.
500 $a Adviser: Tomy Varghese.
502 $a Thesis (Ph.D.)--The University of Wisconsin - Madison, 2015.
520 $a Hepatocellular carcinoma is one of the leading causes of cancer related deaths worldwide. Percutaneous needle-based tumor ablation is a minimally invasive treatment method for liver tumors in patients that are not candidates for surgery. In order to prevent recurrence, it is crucial that the right volume of tissue and a safety margin around the tumor are completely ablated during treatment. Although magnetic resonance imaging and computed X-ray tomography are currently used for monitoring the procedure, ultrasound imaging is potentially safer and more cost-effective and can also provide real-time high frame rate imaging capabilities. Information about tissue stiffness obtained using ultrasound elastography can play an important role in locating the boundary of ablated tissue and help in planning and execution of the ablation procedure.
520 $a The goal of this dissertation is to develop robust signal processing algorithms to delineate ablation boundaries based on stiffness variations estimated from high frame rate radiofrequency ultrasound echo data. Shear wave velocity is used as a surrogate for tissue stiffness. A method called electrode vibration elastography is used where the ablation needle is vibrated using an actuator and acts as a line source for shear waves. The shear wave pulse is tracked in the imaging plane as it travels laterally away from this line source. Model based denoising algorithms are developed to track the shear wave pulse and reconstruct two dimensional (2D) shear wave velocity images.
520 $a In order to generate three dimensional (3D) visualizations of the ablated volume from 2D imaging planes, multiple 2D imaging slices are acquired in a sheaf geometry, with the ablation needle coinciding with the axis of the sheaf. Shear wave velocity information from the individual 2D imaging planes can be used to reconstruct transverse or C-planes that are stacked to generate a 3D visualization. The reconstruction is performed using a penalized least-squares algorithm. A computationally tractable iterative reconstruction algorithm that can handle 3D grids with millions of points is also developed.
590 $a School code: 0262.
650 4 $a Electrical engineering. $3 649834
650 4 $a Biomedical engineering. $3 535387
650 4 $a Medical imaging. $3 3172799
690 $a 0544
690 $a 0541
690 $a 0574
710 2 $a The University of Wisconsin - Madison. $b Electrical Engineering. $3 2095968
773 0 $t Dissertation Abstracts International $g 77-01B(E).
790 $a 0262
791 $a Ph.D.
792 $a 2015
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3721821