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

  • Niladri Shekhar MishraEmail author
  • Sudeb Das
  • Amlan Chakrabarti
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10481)


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.


Image fusion Fuzzy triangular membership function Non-Subsampled Shearlet Transform (i.e. NSST) Pulse-coupled neural network 



The authors would like to thank the anonymous referees for their constructive criticism and valuable suggestions. They also like to thank and 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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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Niladri Shekhar Mishra
    • 1
    Email author
  • Sudeb Das
    • 2
  • Amlan Chakrabarti
    • 3
  1. 1.Department of Electronics and Communication EngineeringNetaji Subhash Engineering CollegeKolkataIndia
  2. 2.Videonetics Technology Private LimitedKolkataIndia
  3. 3.A.K. Choudhury School of Information TechnologyUniversity of CalcuttaKolkataIndia

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