## Abstract

In tomographic image reconstructions, it is often necessary to compute certain statistics of a reconstructed image. These quantities can be used, for example, to analyze the noise properties of a reconstruction. This paper introduces the model-based bootstrapping method to approximate mean and variance-covariance matrix of a reconstruction. This approximation is versatile and can be implemented in different tomographic reconstructions, such as emission and transmission tomographies. This paper also considers the possibility of computational load reduction by a simultaneous multiplicative iterative econstruction algorithm.

Original language | English |
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Title of host publication | Proceedings of the 6th International Symposium on Image and Signal Processing and Analysis, ISPA 2009 |

Editors | Peter Zinterhof, Sven Loncaric, Andreas Uhl, Alberto Carini |

Place of Publication | Piscataway, NJ |

Publisher | Institute of Electrical and Electronics Engineers (IEEE) |

Pages | 145-149 |

Number of pages | 5 |

ISBN (Electronic) | 9789531841344 |

ISBN (Print) | 9789531841351 |

Publication status | Published - 2009 |

Event | 6th International Symposium on Image and Signal Processing and Analysis, ISPA 2009 - Salzburg, Austria Duration: 16 Sep 2009 → 18 Sep 2009 |

### Other

Other | 6th International Symposium on Image and Signal Processing and Analysis, ISPA 2009 |
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Country/Territory | Austria |

City | Salzburg |

Period | 16/09/09 → 18/09/09 |

## Keywords

- Emission and transmission tomography
- Generalized linear model
- Model-based bootstrapping
- Simultaneous reconstructions