A multimodality medical image fusion algorithm based on wavelet transform

Authors:
Jionghua Teng;Xue Wang;Jingzhou Zhang;Suhuan Wang;Pengfei Huo
Affiliations:
College of Automation, Northwestern Polytechnical University, Xi'an;College of Automation, Northwestern Polytechnical University, Xi'an;College of Automation, Northwestern Polytechnical University, Xi'an;College of Automation, Northwestern Polytechnical University, Xi'an;College of Automation, Northwestern Polytechnical University, Xi'an
Venue:
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part II
Year:
2010

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Abstract

According to the characteristics of a medical image, this paper presents a multimodality medical image fusion algorithm based on wavelet transform. For the low-frequency coefficients of the medical image, the fusion algorithm adopts the fusion rule of pixel absolute value maximization; for the high-frequency coefficients, the fusion algorithm uses the fusion rule that combines the regional information entropy contrast degree selection with the weighted averaging method. Then the fusion algorithm obtains the fused medical image with inverse wavelet transform. We select two groups of CT/MRI images and PET/ MRI images to simulate our fusion algorithm and compare its simulation results with the commonly-used wavelet transform fusion algorithm. The simulation results show that our fusion algorithm cannot only preserve more information on a source medical image but also greatly enhance the characteristic and brightness information of a fused medical image, thus being an effective and feasible medical image fusion algorithm.