Probabilistic segmentation propagation from uncertainty in registration.
Proccedings Medical Image Analysis and Understanding (MIUA), 2011.
Available under License : See the attached licence file.
In this paper we propose a novel approach for incorporating measures of spatial uncertainty which are derived from non-rigid registration, into propagated segmentation labels. In current approaches to segmentation via label propagation, a point-estimate of the registration parameters is used. However, this is limited by the registration accuracy achieved. In this work, we derive local measurements of the uncertainty of a non-rigid mapping from a probabilistic registration framework. This allows us to consider the set of probable locations for a segmentation label to hold. We demonstrate the use of this method on the propagation of accurately delineated cortical labels in inter-subject brain MRI using the NIREP dataset. We find that accounting for the spatial uncertainty of the mapping increases the sensitivity of correctly classifying anatomical labels.
|Title:||Probabilistic segmentation propagation from uncertainty in registration|
|Event:||Medical Image Understanding and Analysis 2011, King's College London Thursday 14th - Friday 15th July 2011.|
|Open access status:||An open access version is available from UCL Discovery|
|Additional information:||© 2011. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms.|
|UCL classification:||UCL > School of BEAMS > Faculty of Engineering Science
UCL > School of BEAMS > Faculty of Engineering Science > Medical Physics and Bioengineering
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