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  Incorporating Prior Knowledge on Class Probabilities into Local Similarity Measures for Intermodality Image Registration

Hofmann, M., Schölkopf, B., Bezrukov, I., & Cahill, N. (2009). Incorporating Prior Knowledge on Class Probabilities into Local Similarity Measures for Intermodality Image Registration. In W. Wells, S. Joshi, & K. Pohl (Eds.), MICCAI 2009 Workshop on Probabilistic Models for Medical Image Analysis (PMMIA 2009) (pp. 220-231).

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-C30D-6 Version Permalink: https://hdl.handle.net/21.11116/0000-0002-E53B-A
Genre: Conference Paper

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 Creators:
Hofmann, M1, 2, Author           
Schölkopf, B1, 2, Author           
Bezrukov, I1, 2, Author           
Cahill, ND, Author
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: We present a methodology for incorporating prior knowledge on class probabilities into the registration process. By using knowledge
from the imaging modality, pre-segmentations, and/or probabilistic atlases,
we construct vectors of class probabilities for each image voxel. By
defining new image similarity measures for distribution-valued images,
we show how the class probability images can be nonrigidly registered in
a variational framework. An experiment on nonrigid registration of MR
and CT full-body scans illustrates that the proposed technique outperforms
standard mutual information (MI) and normalized mutual information
(NMI) based registration techniques when measured in terms of
target registration error (TRE) of manually labeled fiducials.

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 Dates: 2009-09
 Publication Status: Published online
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 Rev. Type: -
 Identifiers: BibTex Citekey: 6040
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Title: MICCAI 2009 Workshop on Probabilistic Models for Medical Image Analysis (PMMIA 2009)
Place of Event: London, UK
Start-/End Date: 2009-09-20

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Title: MICCAI 2009 Workshop on Probabilistic Models for Medical Image Analysis (PMMIA 2009)
Source Genre: Proceedings
 Creator(s):
Wells, W, Editor
Joshi, S, Editor
Pohl, K, Editor
Affiliations:
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Publ. Info: -
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 220 - 231 Identifier: -