Skip to main content
SpringerLink
Log in

FWFusion: Fuzzy Whale Fusion model for MRI multimodal image fusion

  • Published:
Sādhanā Aims and scope Submit manuscript

Abstract

Medical treatment and diagnosis require information that is taken from several modalities of images like Magnetic Resonance Imaging (MRI), Computerized Tomography and so on. The information obtained for certain ailments is often incomplete, invisible and lacking in consistent scanner performance. Hence, to overcome these issues in the image modalities, image fusion schemes are developed in the literature. This paper proposes a hybrid algorithm using fuzzy concept and a novel P-Whale algorithm, called Fuzzy Whale Fusion (FWFusion), for the fusion of MRI multimodal images. Two multimodal images from MRI (T1, T1C, T2 and FLAIR) are considered as the source images, which are fed as inputs to a wavelet transform. The transform utilized converts the images into four different bands, which are fused using two newly derived fusion factors, fuzzy fusion and whale fusion, in a weighted function. The proposed P-Whale approach combines Whale Optimization Algorithm (WOA) and Particle Swarm Optimization (PSO) for the effective selection of whale fusion factors. The performance of FWFusion model is compared to those of the existing strategies using Mutual Information (MI), Peak Signal-to-Noise Ratio (PSNR) and Root Mean Squared Error (RMSE), as the evaluation metrics. From the mean performance evaluation, it is observed that the proposed approach can achieve MI of 1.714, RMSE of 1.9 and PSNR of 27.9472.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8

Similar content being viewed by others

References

  1. Wang Z, Ziou D, Armenakis C, Li D and Li Q 2005 A comparative analysis of image fusion methods. IEEE Trans. GeoSci. Remote Sens. 43(5): 1391–1402

    Article  Google Scholar 

  2. Kim Y, Lee C, Han D, Kim Y and Kim Y 2011 Improved additive-wavelet image fusion. IEEE Trans. Geosci. Remote Sens. Lett. 8(2): 263–267

    Article  Google Scholar 

  3. Goshtas A A and Nikolov S 2007 Image fusion: advances in the state of the art. Inf. Fus. 8(2): 114–118

    Article  Google Scholar 

  4. Dammavalam S R, Maddala S and Krishna Prasad M H M 2012 Comparison of fuzzy and neuro-fuzzy image fusion techniques and its applications. Int. J. Comput. Appl. 43(19): 31–37

    Google Scholar 

  5. Dammavalam S R, Maddala S and Krishna Prasad M H M 2012 Quality assessment of pixel level image fusion using fuzzy logic. Int. J. Soft Comput. 3(1): 11–23

    Article  Google Scholar 

  6. Kavitha S and Thyagharajan K K 2017 Efficient DWT-based fusion techniques using genetic algorithm for optimal parameter estimation. J. Soft Comput. 21(12): 3307–3316

    Article  Google Scholar 

  7. James A P and Dasarathy B V 2014 Medical image fusion: a survey of the state-of-the-art. Inf. Fus. 19: 4–19

    Article  Google Scholar 

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

    Article  Google Scholar 

  9. Khalegi B, Khamis A, Karray F O, et al 2013 Multisensor data fusion: a review of the state-of-the-art. Inf. Fus. 14(1): 28–44

    Article  Google Scholar 

  10. Rajkumar S and Kavitha S 2010 Redundancy discrete wavelet transform and contourlet transform for multimodality medical image fusion with quantitative analysis. In: Proceedings of the 3rd IEEE International Conference on Emerging Trends in Engineering and Technology, pp. 134–139

  11. Shah P, Merchant S N and Desai U B 2013 Multifocus and multispectral image fusion based on pixel significance using multiresolution decomposition. Signal Image Video Process. 7(1): 95–109

    Article  Google Scholar 

  12. Bhateja V, Patel H, Krishn A, Sahu A and Lay-Ekuakille A 2015 Multimodal medical image sensor fusion framework using cascade of wavelet and contourlet transform domains. IEEE Sens. J. 15(12) 6783–6790

    Article  Google Scholar 

  13. Yang Y, Park D S, Huang S and Rao N 2010 Medical image fusion via an effective wavelet-based approach. EURASIP J. Adv. Signal Process. 2010: 579341

    Article  Google Scholar 

  14. Bhavana V and Krishnappa H K 2015 Multi-modality medical image fusion using discrete wavelet transform. In: Proceedings of 4th international conference on eco-friendly computing and communication systems, vol. 70, pp. 625–631

  15. Koley S, Galande A, Kelkar B, Sadhu A K, Sarkar D and Chakraborty C 2016 Multispectral MRI image fusion for enhanced visualization of meningioma brain tumors and edema using contourlet transform and fuzzy statistics. J. Med. Biol. Eng. 36(4): 470–484

    Article  Google Scholar 

  16. Srivastava R, Prakash O and Khare A 2016 Local energy-based multimodal medical image fusion in curvelet domain. IET Comput. Vis. 10(6): 513–527

    Article  Google Scholar 

  17. Vijayarajan R 2015 Discrete wavelet transform based principal component averaging fusion for medical images. Int. J. Electron. Commun. 69(6): 896–902

    Article  Google Scholar 

  18. Lu H, Zhang L and Serikawa S 2012 Maximum local energy: an effective approach for multisensor image fusion in beyond wavelet transform domain. Comput. Math. Appl. 64(5): 996–1003

    Article  MATH  Google Scholar 

  19. Xu X, Wang Y and Chen S 2016 Medical image fusion using discrete fractional wavelet transform. Biomed. Signal Process. Control 27: 103–111

    Article  Google Scholar 

  20. De A, Kumar S K, Gunasekaran A and Tiwari M K 2017 Sustainable maritime inventory routing problem with time window constraints. Eng. Appl. Artif. Intell. 61: 77–95

    Article  Google Scholar 

  21. De A, Mamanduru V K R, Gunasekaran A, Subramanian N and Tiwari M K 2016 Composite particle algorithm for sustainable integrated dynamic ship routing and scheduling optimization. Comput. Ind. Eng. 96: 201–215

    Article  Google Scholar 

  22. Maiyar L M and Thakkar J J 2017 A combined tactical and operational deterministic food grain transportation model: particle swarm based optimization approach. Comput. Ind. Eng. 110: 30–42

    Article  Google Scholar 

  23. Irshad H, Kamran M, Siddiqui A B and Hussain A 2009 Image fusion using computational intelligence: a survey. In: Proceedings of the Second International Conference on Environmental and Computer Science, pp. 128–132

  24. Gonzalez R C and Woods R E 2009 Digital image processing. India: Pearson Education

    Google Scholar 

  25. Choi M 2006 A new intensity-hue-saturation fusion approach to image fusion with a tradeoff parameter. IEEE Trans. Geosci. Remote Sens. 44(6): 1672–1682

    Article  Google Scholar 

  26. Nikolov S, Hill P, Bull D and Canagarajah N 2001 Wavelets for image fusion. In: Wavelets in signal and image analysis, vol. 19, pp. 213–241 (chapter)

  27. Mirjalili S and Lewis A 2016 The whale optimization algorithm. Adv. Eng. Softw. 95: 51–67

    Article  Google Scholar 

  28. Chander S, Vijaya P and Dhyani P 2016 Fractional Lion Algorithm – an optimization algorithm for data clustering. J. Comput. Sci. 12(7): 323–340

    Article  Google Scholar 

  29. Chander S, Vijaya P and Dhyani P 2016 MKF-firefly: hybridization of firefly and multiple kernel-based fuzzy C-means algorithm. Int. J. Adv. Res. Comput. Commun. Eng. 5(7): 213–216

    Article  Google Scholar 

  30. Gong Y J, et al 2016 Genetic learning particle swarm optimization. IEEE Trans. Cybernet. 46(10): 2277–2290

    Article  Google Scholar 

  31. https://www.smir.ch/BRATS/Start2015

Download references

Author information

Authors and Affiliations

  1. Department of Electronics and Telecommunication, NDMVPS’s KBT COE, Nashik, 422013, India

    Hanmant Venketrao Patil

  2. Department of Electronics and Telecommunication, Zeal Education Society, Pune, 411041, India

    Suresh D Shirbahadurkar

Authors
  1. Hanmant Venketrao Patil
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Suresh D Shirbahadurkar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hanmant Venketrao Patil.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Patil, H.V., Shirbahadurkar, S.D. FWFusion: Fuzzy Whale Fusion model for MRI multimodal image fusion. Sādhanā 43, 38 (2018). https://doi.org/10.1007/s12046-018-0796-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12046-018-0796-z

Keywords

Search

Navigation