### Abstract

When using a non-rigid registration
scheme, it is possible that bias is
introduced during the registration process
of consecutive sections. This bias can
accumulate when large series of sections
are to be registered and can cause
substantial distortions of the scale space of
individual sections thus leading to
significant measurement bias. This paper
presents an automated scheme based on
Markov Chain Monte Carlo (MCMC)
techniques to estimate and eliminate
registration bias. For this purpose, a
hierarchical model is used based on the
assumption that (a)
each section has the same, independent
probability to be deformed by the
sectioning and therefore the subsequent
registration process and (b) the varying
bias introduced by the registration process
has to be balanced such that the average
section area is preserved forcing the
average scale parameters to have a mean
value of 1.0.

Original language | English |
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Title of host publication | Not Known |

Publication status | Published - 2 Sep 2009 |

Event | 13th International CAIP Conference - University of Münster, Münster, Germany Duration: 2 Sep 2009 → 4 Sep 2009 |

### Conference

Conference | 13th International CAIP Conference |
---|---|

Country | Germany |

City | Münster |

Period | 2/09/09 → 4/09/09 |

## Fingerprint Dive into the research topics of 'MCMC-Based Algorithm to Adjust Scale Bias in Large Series of Electron Microscopical Ultrathin Sections'. Together they form a unique fingerprint.

## Cite this

Zhang, H., Rodriguez, P., Morrow, P., McClean, S., & Saetzler, K. (2009). MCMC-Based Algorithm to Adjust Scale
Bias in Large Series of Electron
Microscopical Ultrathin Sections. In

*Not Known*http://cvpr.uni-muenster.de/CAIP2009/cfp.html