### Abstract

One of the most powerful approach in ultrasound tomography (UT) is making use of distorted Born iterative (DBI) method to reconstruct high quality image in order to help locate and identify tumors more precisely. Due to its iterative nature, it begins with Born approximation as the initial guess. Then, it makes use of the inhomogeneous Greens function, as the kernel function, to alternatively calculate the total field for the forward problem and the scattering function for the inverse problem. One principal computational problem involved is that inverse problem is ill-posed, which will result in divergence of the DBI method if inappropriate regularization is used. This paper presents the regularization with truncated total least square (TTLS) where the adaptive algorithm is used to choose the regularization parameter in each iteration of DBI instead of using a fixed truncated value in all the iterations. In order to prevent the solution from being contaminated by noise, adaptive algorithm truncates the smallest singular values while minimizing the loss of signal obtained from transducers. Numerical simulations demonstrate that the proposed adaptive algorithm in conjunction with TTLS outperform TTLS with fixed truncation parameter by effectively reducing the noise and minimizing the relative error.

Original language | English (US) |
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Title of host publication | Medical Imaging 2019 |

Subtitle of host publication | Ultrasonic Imaging and Tomography |

Editors | Brett C. Byram, Nicole V. Ruiter |

Publisher | SPIE |

ISBN (Electronic) | 9781510625570 |

DOIs | |

State | Published - Jan 1 2019 |

Event | Medical Imaging 2019: Ultrasonic Imaging and Tomography - San Diego, United States Duration: Feb 17 2019 → Feb 18 2019 |

### Publication series

Name | Progress in Biomedical Optics and Imaging - Proceedings of SPIE |
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Volume | 10955 |

ISSN (Print) | 1605-7422 |

### Conference

Conference | Medical Imaging 2019: Ultrasonic Imaging and Tomography |
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Country | United States |

City | San Diego |

Period | 2/17/19 → 2/18/19 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Electronic, Optical and Magnetic Materials
- Atomic and Molecular Physics, and Optics
- Biomaterials
- Radiology Nuclear Medicine and imaging

### Cite this

*Medical Imaging 2019: Ultrasonic Imaging and Tomography*[1095515] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 10955). SPIE. https://doi.org/10.1117/12.2512416

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*Medical Imaging 2019: Ultrasonic Imaging and Tomography.*, 1095515, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 10955, SPIE, Medical Imaging 2019: Ultrasonic Imaging and Tomography, San Diego, United States, 2/17/19. https://doi.org/10.1117/12.2512416

**Adaptive truncated total least square on distorted born iterative method in ultrasound inverse scattering problem.** / Carevia, Anita; Yun, Xingzhao; Almekkawy, Mohamed Khaled.

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

TY - GEN

T1 - Adaptive truncated total least square on distorted born iterative method in ultrasound inverse scattering problem

AU - Carevia, Anita

AU - Yun, Xingzhao

AU - Almekkawy, Mohamed Khaled

PY - 2019/1/1

Y1 - 2019/1/1

N2 - One of the most powerful approach in ultrasound tomography (UT) is making use of distorted Born iterative (DBI) method to reconstruct high quality image in order to help locate and identify tumors more precisely. Due to its iterative nature, it begins with Born approximation as the initial guess. Then, it makes use of the inhomogeneous Greens function, as the kernel function, to alternatively calculate the total field for the forward problem and the scattering function for the inverse problem. One principal computational problem involved is that inverse problem is ill-posed, which will result in divergence of the DBI method if inappropriate regularization is used. This paper presents the regularization with truncated total least square (TTLS) where the adaptive algorithm is used to choose the regularization parameter in each iteration of DBI instead of using a fixed truncated value in all the iterations. In order to prevent the solution from being contaminated by noise, adaptive algorithm truncates the smallest singular values while minimizing the loss of signal obtained from transducers. Numerical simulations demonstrate that the proposed adaptive algorithm in conjunction with TTLS outperform TTLS with fixed truncation parameter by effectively reducing the noise and minimizing the relative error.

AB - One of the most powerful approach in ultrasound tomography (UT) is making use of distorted Born iterative (DBI) method to reconstruct high quality image in order to help locate and identify tumors more precisely. Due to its iterative nature, it begins with Born approximation as the initial guess. Then, it makes use of the inhomogeneous Greens function, as the kernel function, to alternatively calculate the total field for the forward problem and the scattering function for the inverse problem. One principal computational problem involved is that inverse problem is ill-posed, which will result in divergence of the DBI method if inappropriate regularization is used. This paper presents the regularization with truncated total least square (TTLS) where the adaptive algorithm is used to choose the regularization parameter in each iteration of DBI instead of using a fixed truncated value in all the iterations. In order to prevent the solution from being contaminated by noise, adaptive algorithm truncates the smallest singular values while minimizing the loss of signal obtained from transducers. Numerical simulations demonstrate that the proposed adaptive algorithm in conjunction with TTLS outperform TTLS with fixed truncation parameter by effectively reducing the noise and minimizing the relative error.

UR - http://www.scopus.com/inward/record.url?scp=85066634233&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85066634233&partnerID=8YFLogxK

U2 - 10.1117/12.2512416

DO - 10.1117/12.2512416

M3 - Conference contribution

AN - SCOPUS:85066634233

T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE

BT - Medical Imaging 2019

A2 - Byram, Brett C.

A2 - Ruiter, Nicole V.

PB - SPIE

ER -