Abstract
Multimodal medical image fusion techniques are utilized to fuse two images obtained from dissimilar sensors for obtaining additional information. These methods are used to fuse computed tomography (CT) images with magnetic resonance images (MRI), MR-T1 images with MR-T2 images, and MR images with single photon emission computed tomography (SPECT) images. In proposed method, nonsubsampled shearlet transform (NSST) is used for decomposition of source images to attain the low-frequency and high-frequency bands. The low-frequency bands are fused using weighted saliency-based fusion criteria, and high-frequency bands are fused with the help of phase stretch transform (PST) features. Applying inverse NSST operation, fused image is obtained. The results show the proposed method produces better results compared to state-of-the-art methods.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Asghari, M.H., Jalali, B.: Edge detection in digital images using dispersive phase stretch transform. Journal of Biomedical Imaging 2015, 6 (2015)
Bhateja, V., Patel, H., Krishn, A., Sahu, A., Lay-Ekuakille, A.: Multimodal medical image sensor fusion framework using cascade of wavelet and contourlet transform domains. IEEE Sensors Journal 15(12), 6783–6790 (2015)
Bhatnagar, G., Wu, Q.J., Liu, Z.: Directive contrast based multimodal medical image fusion in NSCT domain. IEEE transactions on multimedia 15(5), 1014–1024 (2013)
Burt, P.J., Kolczynski, R.J.: Enhanced image capture through fusion. In: Computer Vision, 1993. Proceedings., Fourth International Conference on. pp. 173–182. IEEE (1993)
Choi, M., Kim, R.Y., Kim, M.G.: The curvelet transform for image fusion. International Society for Photogrammetry and Remote Sensing, ISPRS 2004 35, 59–64 (2004)
Collignon, A., Maes, F., Delaere, D., Vandermeulen, D., Suetens, P., Marchal, G.: Automated multi-modality image registration based on information theory. In: Information processing in medical imaging. vol. 3, pp. 263–274 (1995)
Easley, G., Labate, D., Lim, W.Q.: Sparse directional image representations using the discrete shearlet transform. Applied and Computational Harmonic Analysis 25(1), 25–46 (2008)
Grohs, P., Keiper, S., Kutyniok, G., Schaefer, M.: Alpha molecules: curvelets, shearlets, ridgelets, and beyond. In: SPIE Optical Engineering + Applications. pp. 885804–885804. International Society for Optics and Photonics (2013)
Guo, K., Labate, D.: Optimally sparse multidimensional representation using shearlets. SIAM journal on mathematical analysis 39(1), 298–318 (2007)
Guorong, G., Luping, X., Dongzhu, F.: Multi-focus image fusion based on non-subsampled shearlet transform. IET Image Processing 7(6), 633–639 (2013)
Kaplan, I., Oldenburg, N.E., Meskell, P., Blake, M., Church, P., Holupka, E.J.: Real time MRI-ultrasound image guided stereotactic prostate biopsy. Magnetic resonance imaging 20(3), 295–299 (2002)
Kong, W., Liu, J.: Technique for image fusion based on nonsubsampled shearlet transform and improved pulse-coupled neural network. Optical Engineering 52(1), 017001–017001 (2013)
Li, H., Manjunath, B., Mitra, S.K.: Multisensor image fusion using the wavelet transform. Graphical models and image processing 57(3), 235–245 (1995)
Liu, Y., Liu, S., Wang, Z.: Multi-focus image fusion with dense sift. Information Fusion 23, 139–155 (2015)
Mitianoudis, N., Stathaki, T.: Optimal contrast correction for ICA-based fusion of multimodal images. IEEE sensors journal 8(12), 2016–2026 (2008)
Petrovic, V.S., Xydeas, C.S.: Gradient-based multiresolution image fusion. IEEE Transactions on Image processing 13(2), 228–237 (2004)
Prabhakar, S., Jain, A.K.: Decision-level fusion in fingerprint verification. Pattern Recognition 35(4), 861–874 (2002)
Schoder, H., Yeung, H.W., Gonen, M., Kraus, D., Larson, S.M.: Head and neck cancer: Clinical usefulness and accuracy of pet/ct image fusion 1. Radiology 231(1), 65–72 (2004)
Shih, P., Liu, C.: Comparative assessment of content-based face image retrieval in different color spaces. International Journal of Pattern Recognition and Artificial Intelligence 19(07), 873–893 (2005)
Summers, D.: Harvard whole brain atlas: http://www.med.harvard.edu/aanlib/home.html. Journal of neurology, neurosurgery, and psychiatry 74(3), 288 (2003)
Wang, T., Zhu, Z., Blasch, E.: Bio-inspired adaptive hyperspectral imaging for real-time target tracking. IEEE Sensors Journal 10(3), 647–654 (2010)
Xiao-Bo, Q., Jing-Wen, Y., Hong-Zhi, X., Zi-Qian, Z.: Image fusion algorithm based on spatial frequency-motivated pulse coupled neural networks in nonsubsampled contourlet transform domain. Acta Automatica Sinica 34(12), 1508–1514 (2008)
Xydeas, C., Petrovic, V.: Objective image fusion performance measure. Electronics letters 36(4), 308–309 (2000)
Yang, C., Zhang, J.Q., Wang, X.R., Liu, X.: A novel similarity based quality metric for image fusion. Information Fusion 9(2), 156–160 (2008)
Yang, Y., Que, Y., Huang, S., Lin, P.: Multimodal sensor medical image fusion based on type-2 fuzzy logic in nsct domain. IEEE Sensors Journal 16(10), 3735–3745 (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Vishwakarma, A., Bhuyan, M.K., Iwahori, Y. (2018). An Efficient Algorithm for Medical Image Fusion Using Nonsubsampled Shearlet Transform. In: Chaudhuri, B., Kankanhalli, M., Raman, B. (eds) Proceedings of 2nd International Conference on Computer Vision & Image Processing . Advances in Intelligent Systems and Computing, vol 703. Springer, Singapore. https://doi.org/10.1007/978-981-10-7895-8_19
Download citation
DOI: https://doi.org/10.1007/978-981-10-7895-8_19
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-7894-1
Online ISBN: 978-981-10-7895-8
eBook Packages: EngineeringEngineering (R0)