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2010

Automatic Parameter Selection for Multimodal Image Registration

8 years 5 months ago
Automatic Parameter Selection for Multimodal Image Registration
Over the past ten years similarity measures based on intensity distributions have become state-of-the-art in automatic multimodal image registration. An implementation for clinical usage has to support a plurality of images. However, a generally applicable parameter configuration for the number and sizes of histogram bins, optimal Parzen-window kernel widths or background thresholds cannot be found. This explains why various research groups present partly contradictory empirical proposals for these parameters. This paper proposes a set of data-driven estimation schemes for a parameter-free implementation that eliminates major caveats of heuristic trial and error. We present the following novel approaches: a new coincidence weighting scheme to reduce the influence of background noise on the similarity measure in combination with Max-Lloyd requantization, and a tradeoff for the automatic estimation of the number of histogram bins. These methods have been integrated into a state-of-the-ar...
Dieter A. Hahn, Volker Daum, Joachim Hornegger
Added 22 May 2011
Updated 22 May 2011
Type Journal
Year 2010
Where TMI
Authors Dieter A. Hahn, Volker Daum, Joachim Hornegger
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