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Non-rigid image registration using local histogram-based features

Authors: Yishan, Luo; Albert C S, Chung;

Non-rigid image registration using local histogram-based features

Abstract

This paper proposes a new non-rigid image registration method based on the formulation of the Demons algorithm. The proposed method utilizes combined geometric moments of local histogram to form new feature images. It greatly improves the accuracy of the original Demons algorithm, which is easy to get trapped at local minima during optimization. The local histogram-based features are rotation invariant and can capture sufficient spatial image information. During the registration process, local histogram-based feature images are built to substitute the original intensity images. This can reduce the possibility of being trapped at local solutions, and consequently improve the registration accuracy. The experimental results on both the synthetic image and real MRI image show that the proposed method can achieve higher accuracy than the Demons algorithm especially when the images are noisy.

Related Organizations
Keywords

Brain, Reproducibility of Results, Image Enhancement, Magnetic Resonance Imaging, Sensitivity and Specificity, Pattern Recognition, Automated, Subtraction Technique, Image Interpretation, Computer-Assisted, Humans, Algorithms

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Powered by OpenAIRE graph
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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!
2
Average
Average
Average
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