NDLI: Medical image fusion using discrete wavelet transform and lifting scheme

Content Provider	IEEE Xplore Digital Library
Author	Akbarpour, T. Shamsi, M. Daneshvar, S.
Copyright Year	2015
Description	Author affiliation: Electrical and Computer Engineering Faculty, Tabriz University, Tabriz, Iran (Daneshvar, S.) \|\| Electrical Engineering Faculty, Sahand University of Technology, Tabriz, Iran (Shamsi, M.) \|\| Electrical Engineering Faculty, Sahand University of technology, Tabriz, Iran (Akbarpour, T.)
Abstract	Multiple sclerosis (MS) is an inflammatory disease of central nervous system. Magnetic resonance (MR) images play an important role in diagnosis of MS because of the ability in detection of white matter lesions. Proper detection of lesions and their boundaries is crucial for diagnosis. T1 weighted images are the most preferred modal in diagnosis, but enriching them with information of other modals could increase accuracy of lesion detection and thus diagnosis. In this paper a new method based on lifting scheme is suggested to fuse modals of MR. in this algorithm, lifting wavelet transform is used to decompose source images into different subbands. Different fusion rules are applied to fuse subbands and achieve fused image. Numerical and visual analyses prove efficiency of propped method in gathering complemental information of source images in one image.
Starting Page	293
Ending Page	298
File Size	664729
Page Count	6
File Format	PDF
e-ISBN	9781467393515
DOI	10.1109/ICBME.2015.7404158
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-11-25
Publisher Place	Iran
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Measurement Multiple sclerosis Quality metric Lifting scheme Lesions Multiresolution analysis Standards Magnetic resonance image Mutual information Wavelet coefficients
Content Type	Text
Resource Type	Article

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