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Algorithms and calibration technique...

Colgan, Timothy J.

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Algorithms and calibration techniques for high resolution microwave breast imaging.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Algorithms and calibration techniques for high resolution microwave breast imaging./
作者:	Colgan, Timothy J.
面頁冊數:	99 p.
附註:	Source: Dissertation Abstracts International, Volume: 77-10(E), Section: B.
Contained By:	Dissertation Abstracts International77-10B(E).
標題:	Electrical engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10128906
ISBN:	9781339868844

Algorithms and calibration techniques for high resolution microwave breast imaging.
Colgan, Timothy J.

Algorithms and calibration techniques for high resolution microwave breast imaging. - 99 p.

Source: Dissertation Abstracts International, Volume: 77-10(E), Section: B.

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

Microwave breast imaging is being investigated as a low cost, non-ionizing, and widely available imaging modality for breast cancer risk assessment, treatment monitoring, and tumor identification. The dielectric properties of the breast, which are linked to the tissue composition, are iteratively reconstructed using model-based inverse scattering algorithms. However, conventional microwave imaging methods have significant limitations in terms of resolution and experimental performance. Common microwave imaging methods have moderate-to-low resolution that distorts boundaries between different tissue types. Also, any errors in the simulated model of the array setup can corrupt the iterative process of these algorithms and degrade experimental imaging performance.

ISBN: 9781339868844Subjects--Topical Terms:

649834
Electrical engineering.

Algorithms and calibration techniques for high resolution microwave breast imaging.
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245 1 0 $a Algorithms and calibration techniques for high resolution microwave breast imaging.
300 $a 99 p.
500 $a Source: Dissertation Abstracts International, Volume: 77-10(E), Section: B.
500 $a Advisers: Barry D. Van Veen; Susan C. Hagness.
502 $a Thesis (Ph.D.)--The University of Wisconsin - Madison, 2015.
520 $a Microwave breast imaging is being investigated as a low cost, non-ionizing, and widely available imaging modality for breast cancer risk assessment, treatment monitoring, and tumor identification. The dielectric properties of the breast, which are linked to the tissue composition, are iteratively reconstructed using model-based inverse scattering algorithms. However, conventional microwave imaging methods have significant limitations in terms of resolution and experimental performance. Common microwave imaging methods have moderate-to-low resolution that distorts boundaries between different tissue types. Also, any errors in the simulated model of the array setup can corrupt the iterative process of these algorithms and degrade experimental imaging performance.
520 $a Numerical 2D microwave imaging studies demonstrate that the use of a level set method preserves the natural boundary between tissue types resulting in a higher resolution reconstruction of breast structure. Previously proposed level set imaging algorithms have a high computational cost and are impractical in 3D. I developed a computationally tractable 3D microwave imaging algorithm based on level sets and assessed its efficacy for microwave imaging by investigating its performance with evaluating breast density. The density estimates from my level set algorithm are more accurate than those of conventional microwave imaging, and the accuracy is greater than that reported for mammographic density estimation. These results demonstrate the feasibility of high resolution 3D microwave breast imaging using a level set method.
520 $a I also developed a quantitative metric for determining the amount of model error when modeling an experimental array and predicting the impact model error will have on microwave breast imaging. I demonstrate the use of this metric to evaluate experimental imaging performance, experimental calibration, and the performance of different imaging algorithms in the presence of model error. These results demonstrate the efficacy of this metric for improving the performance of microwave imaging in a clinical environment.
520 $a Finally, I present some of my experimental calibration and imaging results for microwave imaging. These include an analysis of experimental calibration techniques, imaging results with different experimental phantoms, and imaging algorithms designed to perform better experimentally.
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
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710 2 $a The University of Wisconsin - Madison. $b Electrical Engineering. $3 2095968
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791 $a Ph.D.
792 $a 2015
793 $a English
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