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Knowledge-based medical image registration

Authors: null Hui-Hua Wen; null Wei-Chung Lin; null Chin-Tu Chen;

Knowledge-based medical image registration

Abstract

Describes a new framework for surface-based medical image registration. By implementing a fuzzy logic system, this method allows the incorporation of human expert knowledge to evaluate the confidence level of two matching points using their multiple local image properties such as gradient direction and curvature. The proposed technique can be applied to both intra- and inter-subject medical image registration. It can also relax the performance requirement on the contour extraction process.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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