Abstract
Medical images coming from different sources can often provide different information. So, combining two or more co-registered multimodal medical images into a single image (image fusion) is an important support to the medical diagnosis. Most of the used image fusion techniques are based on the Multiresolution Analysis (MRA), which is able to decompose an image into several components at different scales. This paper presents a novel Wavelet-based method to fuse medical images according to the MRA approach, that aims to put the right “semantic” content in the fused image by applying two different quality indexes: variance and modulus maxima. Experimental tests show very encouraging results in terms of both quantitative and qualitative evaluations.
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© 2007 Springer-Verlag Berlin Heidelberg
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Alfano, B., Ciampi, M., De Pietro, G. (2007). A Wavelet-Based Algorithm for Multimodal Medical Image Fusion. In: Falcidieno, B., Spagnuolo, M., Avrithis, Y., Kompatsiaris, I., Buitelaar, P. (eds) Semantic Multimedia. SAMT 2007. Lecture Notes in Computer Science, vol 4816. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77051-0_13
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DOI: https://doi.org/10.1007/978-3-540-77051-0_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77033-6
Online ISBN: 978-3-540-77051-0
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