Using Filter Factors for Regularization in Ultrasound Tomography

Anita Carevic; Ali E. Abdou; Jesse Barlow; Mohamed Almekkawy

doi:10.1109/EMBC.2018.8512447

Using Filter Factors for Regularization in Ultrasound Tomography

Anita Carevic
, Ali E. Abdou
, Jesse Barlow
, Mohamed Almekkawy

Computer Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

9 Scopus citations

Abstract

The motivation for ultrasound tomography is the location and identification of malignant human breast tissues for the purpose of detecting breast cancer. Although mammography is widely used for breast cancer detection, it has a high false positive rate and does not always accurately separate malignant tissue from benign tissue. Ultrasound tomography is used to compensate for these shortcomings. The computational model for ultrasound tomography is based upon solving an inverse scattering problem by finding the approximate total field and unknown scattering function using an iterative method. The principal computational problem involved is the solution of an ill-conditioned linear system, Xy\approx b, arising from an ill-posed problem written as an integral equation. In this paper, we explore the DSVD and the DGSVD regularization methods to solve the inverse scattering problem. The DGSVD algorithm gives better results than the DSVD algorithm when we introduce noise in either one or both sides of the linear system Xy\approx b.

Original language	English (US)
Title of host publication	40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	895-898
Number of pages	4
ISBN (Electronic)	9781538636466
DOIs	https://doi.org/10.1109/EMBC.2018.8512447
State	Published - Oct 26 2018
Event	40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 - Honolulu, United States Duration: Jul 18 2018 → Jul 21 2018

Publication series

Name	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume	2018-July
ISSN (Print)	1557-170X

Other

Other	40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
Country/Territory	United States
City	Honolulu
Period	7/18/18 → 7/21/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

Signal Processing
Biomedical Engineering
Computer Vision and Pattern Recognition
Health Informatics

Access to Document

10.1109/EMBC.2018.8512447

Cite this

Carevic, A., Abdou, A. E., Barlow, J., & Almekkawy, M. (2018). Using Filter Factors for Regularization in Ultrasound Tomography. In 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 (pp. 895-898). Article 8512447 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2018-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2018.8512447

Carevic, Anita ; Abdou, Ali E. ; Barlow, Jesse et al. / Using Filter Factors for Regularization in Ultrasound Tomography. 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 895-898 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

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title = "Using Filter Factors for Regularization in Ultrasound Tomography",

abstract = "The motivation for ultrasound tomography is the location and identification of malignant human breast tissues for the purpose of detecting breast cancer. Although mammography is widely used for breast cancer detection, it has a high false positive rate and does not always accurately separate malignant tissue from benign tissue. Ultrasound tomography is used to compensate for these shortcomings. The computational model for ultrasound tomography is based upon solving an inverse scattering problem by finding the approximate total field and unknown scattering function using an iterative method. The principal computational problem involved is the solution of an ill-conditioned linear system, Xy\textbackslash{}approx b, arising from an ill-posed problem written as an integral equation. In this paper, we explore the DSVD and the DGSVD regularization methods to solve the inverse scattering problem. The DGSVD algorithm gives better results than the DSVD algorithm when we introduce noise in either one or both sides of the linear system Xy\textbackslash{}approx b.",

author = "Anita Carevic and Abdou, \{Ali E.\} and Jesse Barlow and Mohamed Almekkawy",

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doi = "10.1109/EMBC.2018.8512447",

language = "English (US)",

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Carevic, A, Abdou, AE, Barlow, J & Almekkawy, M 2018, Using Filter Factors for Regularization in Ultrasound Tomography. in 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018., 8512447, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, vol. 2018-July, Institute of Electrical and Electronics Engineers Inc., pp. 895-898, 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018, Honolulu, United States, 7/18/18. https://doi.org/10.1109/EMBC.2018.8512447

Using Filter Factors for Regularization in Ultrasound Tomography. / Carevic, Anita; Abdou, Ali E.; Barlow, Jesse et al.
40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 895-898 8512447 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2018-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

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AU - Barlow, Jesse

AU - Almekkawy, Mohamed

PY - 2018/10/26

Y1 - 2018/10/26

N2 - The motivation for ultrasound tomography is the location and identification of malignant human breast tissues for the purpose of detecting breast cancer. Although mammography is widely used for breast cancer detection, it has a high false positive rate and does not always accurately separate malignant tissue from benign tissue. Ultrasound tomography is used to compensate for these shortcomings. The computational model for ultrasound tomography is based upon solving an inverse scattering problem by finding the approximate total field and unknown scattering function using an iterative method. The principal computational problem involved is the solution of an ill-conditioned linear system, Xy\approx b, arising from an ill-posed problem written as an integral equation. In this paper, we explore the DSVD and the DGSVD regularization methods to solve the inverse scattering problem. The DGSVD algorithm gives better results than the DSVD algorithm when we introduce noise in either one or both sides of the linear system Xy\approx b.

AB - The motivation for ultrasound tomography is the location and identification of malignant human breast tissues for the purpose of detecting breast cancer. Although mammography is widely used for breast cancer detection, it has a high false positive rate and does not always accurately separate malignant tissue from benign tissue. Ultrasound tomography is used to compensate for these shortcomings. The computational model for ultrasound tomography is based upon solving an inverse scattering problem by finding the approximate total field and unknown scattering function using an iterative method. The principal computational problem involved is the solution of an ill-conditioned linear system, Xy\approx b, arising from an ill-posed problem written as an integral equation. In this paper, we explore the DSVD and the DGSVD regularization methods to solve the inverse scattering problem. The DGSVD algorithm gives better results than the DSVD algorithm when we introduce noise in either one or both sides of the linear system Xy\approx b.

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Carevic A, Abdou AE, Barlow J, Almekkawy M. Using Filter Factors for Regularization in Ultrasound Tomography. In 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 895-898. 8512447. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). doi: 10.1109/EMBC.2018.8512447

Using Filter Factors for Regularization in Ultrasound Tomography

Abstract

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UN SDGs

All Science Journal Classification (ASJC) codes

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