2017 JRNL PP Jiao Du - 1.pdf
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Terbatas  Irwan Sofiyan
» Gedung UPT Perpustakaan
Terbatas  Irwan Sofiyan
» Gedung UPT Perpustakaan
A novel method for performing anatomical magnetic
resonance imaging-functional (positron emission tomography
or single photon emission computed tomography) image
fusion is presented. The method merges specific feature information
from input image signals of a single or multiple medical
imaging modalities into a single fused image, while preserving
more information and generating less distortion. The proposed
method uses a local Laplacian filtering-based technique realized
through a novel multi-scale system architecture. First, the input
images are generated in a multi-scale image representation and
are processed using local Laplacian filtering. Second, at each
scale, the decomposed images are combined to produce fused
approximate images using a local energy maximum scheme
and produce the fused residual images using an information
of interest-based scheme. Finally, a fused image is obtained
using a reconstruction process that is analogous to that of
conventional Laplacian pyramid transform. Experimental results
computed using individual multi-scale analysis-based decomposition
schemes or fusion rules clearly demonstrate the superiority
of the proposed method through subjective observation as well as
objective metrics. Furthermore, the proposed method can obtain
better performance, compared with the state-of-the-art fusion
methods.