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Cited by 795

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Multi-modality image registration by maximization of mutual information

Maes, F., Collignon, A., Vandermeulen, D., Marchal, G., Suetens, P.·1996·Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis

Abstract

Mutual information of image intensities has been proposed as a new matching criterion for automated multi-modality image registration. In this paper the authors give experimental evidence of the power and the generality of the mutual information criterion by showing results for various applications involving CT, MR and PET images. The authors' results illustrate the large applicability of the approach and demonstrate its high suitability for routine use in clinical practice.

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Crossref · 10.1109/mmbia.1996.534053

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Metadata

Authors
Maes, F., Collignon, A., Vandermeulen, D., Marchal, G., & Suetens, P.
Venue
Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis
Publisher
IEEE
Published
1996
Pages
14-22
OpenAlex
W2129941787
Cited by
795
References
1
FWCI
8.15
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Multi-modality image registration by maximization of mutual information. https://app.cochat.ai/papers/10.1109/mmbia.1996.534053
The paper
Maes, F., Collignon, A., Vandermeulen, D., Marchal, G., & Suetens, P. (1996). Multi-modality image registration by maximization of mutual information. Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis. https://doi.org/10.1109/mmbia.1996.534053

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.