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Proceedings Paper

A framework for parameter optimization in mutual information (MI)-based registration algorithms
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Paper Abstract

In this paper, we present a framework that one could use to set optimized parameter values, while performing image registration using mutual information as a metric to be maximized. Our experiment details these steps for the registration of X-ray Computer Tomography (CT) images with Positron Emission Tomography (PET) images. Selection of different parameters that influence the mutual information between two images is crucial for both accuracy and speed of registration. These implementation issues need to be handled in an orderly fashion by designing experiments in their operating ranges. The conclusions from this study seem vital towards obtaining allowable parameter range for a fusion software.

Paper Details

Date Published: 10 March 2006
PDF: 8 pages
Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61442Q (10 March 2006); doi: 10.1117/12.653137
Show Author Affiliations
Girish Gopalakrishnan, GE Global Research (India)
S. V. Bharath Kumar, GE Global Research (India)
Rakesh Mullick, GE Global Research (India)
Ajay Narayanan, GE Global Research (India)
Srikanth Suryanarayanan, GE Global Research (India)


Published in SPIE Proceedings Vol. 6144:
Medical Imaging 2006: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

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