### Abstract

Reflection mode diffraction tomography (DT) is an inversion scheme used to reconstruct the spatially variant refractive index distribution of a scattering object. We propose a linear strategy that makes use of the statistically complementary information inherent in the reflected scattered data to achieve a bias-free reduction of the image variance in two dimensional (2D) reflection mode DT. We derive infinite classes of estimation methods that can estimate the 2D Radon transform of the (band-pass filtered) scattering object function from the reflected scattered data. When the insonifying source is broadband we demonstrate that incorporation of the statistically complementary information generated by each frequency in the incident spectrum can further reduce the variance of the images reconstructed using different estimation methods.

Original language | English (US) |
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Title of host publication | Proceedings of the IEEE Ultrasonics Symposium |

Publisher | IEEE |

Pages | 839-842 |

Number of pages | 4 |

Volume | 1 |

State | Published - 1998 |

Externally published | Yes |

Event | Proceedings of the 1998 International Ultrasonics Symposium - Sendai, Miyagi, Jpn Duration: Oct 5 1998 → Oct 8 1998 |

### Other

Other | Proceedings of the 1998 International Ultrasonics Symposium |
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City | Sendai, Miyagi, Jpn |

Period | 10/5/98 → 10/8/98 |

### Fingerprint

### ASJC Scopus subject areas

- Engineering(all)

### Cite this

*Proceedings of the IEEE Ultrasonics Symposium*(Vol. 1, pp. 839-842). IEEE.

**New classes of reconstruction methods in reflection mode diffraction tomography.** / Anastasio, Mark A.; Kupinski, Matthew A; Pan, Xiaochuan.

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

*Proceedings of the IEEE Ultrasonics Symposium.*vol. 1, IEEE, pp. 839-842, Proceedings of the 1998 International Ultrasonics Symposium, Sendai, Miyagi, Jpn, 10/5/98.

}

TY - CHAP

T1 - New classes of reconstruction methods in reflection mode diffraction tomography

AU - Anastasio, Mark A.

AU - Kupinski, Matthew A

AU - Pan, Xiaochuan

PY - 1998

Y1 - 1998

N2 - Reflection mode diffraction tomography (DT) is an inversion scheme used to reconstruct the spatially variant refractive index distribution of a scattering object. We propose a linear strategy that makes use of the statistically complementary information inherent in the reflected scattered data to achieve a bias-free reduction of the image variance in two dimensional (2D) reflection mode DT. We derive infinite classes of estimation methods that can estimate the 2D Radon transform of the (band-pass filtered) scattering object function from the reflected scattered data. When the insonifying source is broadband we demonstrate that incorporation of the statistically complementary information generated by each frequency in the incident spectrum can further reduce the variance of the images reconstructed using different estimation methods.

AB - Reflection mode diffraction tomography (DT) is an inversion scheme used to reconstruct the spatially variant refractive index distribution of a scattering object. We propose a linear strategy that makes use of the statistically complementary information inherent in the reflected scattered data to achieve a bias-free reduction of the image variance in two dimensional (2D) reflection mode DT. We derive infinite classes of estimation methods that can estimate the 2D Radon transform of the (band-pass filtered) scattering object function from the reflected scattered data. When the insonifying source is broadband we demonstrate that incorporation of the statistically complementary information generated by each frequency in the incident spectrum can further reduce the variance of the images reconstructed using different estimation methods.

UR - http://www.scopus.com/inward/record.url?scp=0032273015&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0032273015&partnerID=8YFLogxK

M3 - Chapter

AN - SCOPUS:0032273015

VL - 1

SP - 839

EP - 842

BT - Proceedings of the IEEE Ultrasonics Symposium

PB - IEEE

ER -