Unifying Encoding of Spatial Information in Mutual Information for Nonrigid Registration

Authors:
Xiahai Zhuang;David J. Hawkes;Sebastien Ourselin
Affiliations:
Centre for Medical Image Computing, Medical Physics & Bioengineering Department, University College London, UK WC1E 6BT;Centre for Medical Image Computing, Medical Physics & Bioengineering Department, University College London, UK WC1E 6BT;Centre for Medical Image Computing, Medical Physics & Bioengineering Department, University College London, UK WC1E 6BT
Venue:
IPMI '09 Proceedings of the 21st International Conference on Information Processing in Medical Imaging
Year:
2009

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Abstract

As encoding spatial information into mutual information (MI) can improve the nonrigid registration against bias fields where the conventional MI is challenged, we propose to unify this encoding into the computation of the joint probability distribution function (PDF). The PDF is computed based on local volumes while the global intensity information is also incorporated to maintain the global intensity class linkage. We demonstrate this computation method can unify the PDF computation in regional MI, conditional MI, and the conventional MI. We then derive two categories of methods and apply them to different registration tasks. The experimental results demonstrate that both categories can significantly improve the registration.