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Shearlet Based Medical Image Fusion Using Pulse-Coupled Neural Network with Fuzzy Memberships

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Computer Vision, Graphics, and Image Processing (ICVGIP 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10481))

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Abstract

In this article, we propose a novel multimodal Medical Image Fusion (MIF) method based on a neuro-fuzzy technique in the transform (Non-Subsampled Shearlet Transform (NSST)) domain for spatially registered, multi-modal medical images. The source medical images are first decomposed by NSST. The low-frequency subbands (LFSs) are fused using the Max-selection rule. Fuzzy triangular memberships are derived from a specific neighborhood-region of each high-frequency coefficient. Then they (high-frequency subbands, HFSs) are fused using a biologically inspired neural network (Pulse Coupled Neural Network (PCNN)) according to our newly proposed rule. Then inverse NSST (INSST) is applied to the fused coefficients to get the fused image. Visual and quantitative analysis and comparisons with state-of-the-art MIF techniques show the effectiveness of the proposed scheme in fusing multimodality medical images.

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References

  1. Barra, V., Boire, J.Y.: A general framework for the fusion of anatomical and functional medical images. NeuroImage 13(3), 410–424 (2001)

    Article  Google Scholar 

  2. Bezdek, J.C.: Fuzzy models-what are they, and why? [editorial]. IEEE Trans. Fuzzy Syst. 1(1), 1–6 (1993)

    Article  MathSciNet  Google Scholar 

  3. da Cunha, A.L., Zhou, J., Do, M.N.: The nonsubsampled contourlet transform: theory, design, and applications. IEEE Trans. Image Process. 15(10), 3089–3101 (2006)

    Article  Google Scholar 

  4. Das, S., Kundu, M.K.: NSCT-based multimodal medical image fusion using pulse-coupled neural network and modified spatial frequency. Med. Biol. Eng. Comput. 50(10), 1105–1114 (2012)

    Article  Google Scholar 

  5. Easley, G., Labate, D., Lim, W.Q.: Sparse directional image representations using the discrete shearlet transform. Appl. Comput. Harm. Anal. 25, 25–46 (2008)

    Article  MATH  MathSciNet  Google Scholar 

  6. James, A.P., Dasarathy, B.V.: Medical image fusion: a survey of the state of the art. Inf. Fusion 19, 4–19 (2014)

    Article  Google Scholar 

  7. Johnson, J.L., Padgett, M.L.: PCNN models and applications. IEEE Trans. Neural Netw. 10(3), 480–498 (1999)

    Article  Google Scholar 

  8. Pedrycz, W.: Why triangular membership functions? Fuzzy Sets Syst. 64(1), 21–30 (1994)

    Article  MathSciNet  Google Scholar 

  9. Singh, S., Gupta, D., Anand, R.S., Kumar, V.: Nonsubsampled shearlet based CT and MR medical image fusion using biologically inspired spiking neural network. Biomed. Sig. Process. Control 18, 91–101 (2015)

    Article  Google Scholar 

  10. Wang, Z., Ma, Y.: Medical image fusion using m-PCNN. Inf. Fusion 9(2), 176–185 (2008)

    Article  Google Scholar 

  11. Wang, Z., Ma, Y., Cheng, F., Yang, L.: Review of pulse-coupled neural networks. Image Vis. Comput. 28(1), 5–13 (2010)

    Article  Google Scholar 

  12. Yang, L., Guo, B.L., Ni, W.: Multimodality medical image fusion based on multiscale geometric analysis of contourlet transform. Neurocomputing 72(1–3), 203–211 (2008)

    Article  Google Scholar 

  13. Yang, Y., Park, D.S., Huang, S., Rao, N.: Medical image fusion via an effective wavelet-based approach. EURASIP J. Adv. Sig. Process. 2010, 44:1–44:13 (2010)

    Google Scholar 

  14. Yue, S., Wu, T., Pan, J., Wang, H.: Fuzzy clustering based ET image fusion. Inf. Fusion 14, 487–497 (2013)

    Article  Google Scholar 

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Acknowledgement

The authors would like to thank the anonymous referees for their constructive criticism and valuable suggestions. They also like to thank http://www.imagefusion.org/ and http://www.med.harvard.edu/aanlib/home.html for providing the source medical images. Prof. (Dr.) Amlan Chakrabarti likes to thank “CoE in Systems Biology and Biomedical Engineering, University of Calcutta supported by TEQIP-II Project” for supporting the research work.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Netaji Subhash Engineering College, Kolkata, 700152, India

    Niladri Shekhar Mishra

  2. Videonetics Technology Private Limited, B.P. Block, Sector V, Salt Lake City, Kolkata, 700091, India

    Sudeb Das

  3. A.K. Choudhury School of Information Technology, University of Calcutta, Kolkata, 700009, India

    Amlan Chakrabarti

Authors
  1. Niladri Shekhar Mishra
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  2. Sudeb Das
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  3. Amlan Chakrabarti
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Corresponding author

Correspondence to Niladri Shekhar Mishra .

Editor information

Editors and Affiliations

  1. Indian Institute of Information Technology, Chittoor, India

    Snehasis Mukherjee

  2. GE Global Research, Bangalore, India

    Suvadip Mukherjee

  3. Indian Statistical Institute, Kolkata, India

    Dipti Prasad Mukherjee

  4. International Institute of Information Technology, Hyderabad, India

    Jayanthi Sivaswamy

  5. Indian Institute of Technology Bombay, Mumbai, India

    Suyash Awate

  6. CEDAR, Buffalo, New York, USA

    Srirangaraj Setlur

  7. International Institute of Information Technology, Hyderabad, India

    Anoop M. Namboodiri

  8. CSIR-CEERI, Pilani, Rajasthan, India

    Santanu Chaudhury

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Mishra, N.S., Das, S., Chakrabarti, A. (2017). Shearlet Based Medical Image Fusion Using Pulse-Coupled Neural Network with Fuzzy Memberships. In: Mukherjee, S., et al. Computer Vision, Graphics, and Image Processing. ICVGIP 2016. Lecture Notes in Computer Science(), vol 10481. Springer, Cham. https://doi.org/10.1007/978-3-319-68124-5_29

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  • DOI: https://doi.org/10.1007/978-3-319-68124-5_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68123-8

  • Online ISBN: 978-3-319-68124-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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