Medical Image Fusion Schemes Using Contourlet Transform and PCA Bases
DOI:
https://doi.org/10.51983/ajes-2015.4.1.1932Abstract
Fusion imaging is one of the most modern, accurate and useful diagnostic techniques in medical imagin g today. The new technology has made a clear difference in patient care by compressing the time between diagnosis and treatment. Although image fusion can have different purposes, the main aim of fusion is spatial resolution enhancement or image sharpening. Also known as integrated imaging, it provides a computer link that allows for the combination of multimodal medical images into a single image with more complete and accurate description of the same object. The benefits are even more profound in combining anatomical imaging modalities with functional ones. For example, PET-CT in lung cancer, MRI-PET in brain tumors, SPECT-CT in abdominal studies and ultrasound images-MRI for vascular blood flow . outcome of MRI-CT image fusion has been shown to be able to assist in planning surgical procedure. Mainly, medical image fusion try to solve the issue of where there is no single modality provides both anatomical and functional information. Further more information provided by different modalities may be in agreement or in complementary nature.
References
M. Aguilar and J. R. New, "Fusion of multi-modality volumetric medical imagery," in Proceedings of the Fifth International Conference on Information Fusion, vol. 2, pp. 1206-1212, Annapolis, MD, 2002, ISBN 0-9721844-1-4.
N. Al-Azzawi, H. A. M. Sakim, W. A. K. W. Abdullah, and H. Ibrahim, "Medical image fusion scheme using complex contourlet transform based on PCA," in Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC2009, pp. 5813-5816, Hilton Minneapolis, Minnesota, USA, 2-6 September 2009, ISBN 1557-170X.
R. H. Bamberger and M. J. T. Smith, "A filter bank for the directional decomposition of images: Theory and design," IEEE Transactions on Signal Processing, vol. 40, no. 4, pp. 882-893, 1992, ISSN 1053587X.
K. Baum, M. Helguera, and A. Krol, "Fusion viewer: A new tool for fusion and visualization of multimodal medical data sets," Journal of Digital Imaging, vol. 21, pp. 59-68, 2008, ISSN 0897-1889.
A. Roche, G. Malandain, X. Pennec, and N. Ayache, "The correlation ratio as a new similarity measure for multimodal image registration," in Medical Image Computing and Computer-Assisted Intervention - MICCAI’98, vol. 1496, pp. 1115-1124, Springer Berlin Heidelberg, 1998, ISBN 978-3-540-65136-9.
V. G. Ruiz, J. J. Fernández, M. F. López, and I. García, "Progressive image transmission in telemicroscopy: A quantitative approach for electron microscopy images of biological specimens," Real-Time Imaging, vol. 8, no. 6, pp. 519-544, 2002, ISSN 1077-2014.
L. Yang, B. L. Guo, and W. Ni, "Multimodality medical image fusion based on multiscale geometric analysis of contourlet transform," Neurocomputing, vol. 72, no. 1-3, pp. 203-211, 2008, ISSN 0925-2312.
C. Yong, H. You, and Y. Chaolong, "CT and MRI image fusion based on contourlet using a novel rule," in The 2nd International Conference on Bioinformatics and Biomedical Engineering, ICBBE 2008, pp. 2064-2067, Shanghai, 16-18 May 2008, ISBN 978-1-4244-1747-6.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2015 The Research Publication
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
