A New Approach for Multimodal Medical Image Fusion using PDE-based Technique

A New Approach for Multimodal Medical Image Fusion using PDE-based Technique

Authors

  • Gargi Trivedi CVM University
  • Rajesh Sanghvi

DOI:

https://doi.org/10.55766/sujst-2023-04-e0843

Keywords:

Image fusion, partial differential equation, principal component analysis

Abstract

Accurate diagnosis of diseases is essential for effective medical treatment, and medical image fusion plays a crucial role in achieving this goal. This article proposes a novel technique for multimodal medical image fusion based on fourth order PDE-based techniques. The proposed technique uses inputted CT and brain MRI images, and applies a PDE-based technique for noise reduction and edge preservation. Subsequently, a computed fusion rule using principal component analysis is applied to generate a fused image of the brain that presents clear and essential components for medical diagnosis and analysis. The article provides a comparative study of the proposed technique with other existing techniques, demonstrating its optimal performance. The proposed technique can significantly enhance medical image diagnosis and analysis for accurate disease detection and treatment.

References

Bavirisetti, D.P., Xiao, G., and Liu, G. (2019). Multi-sensor image fusion based on fourth order partial differential equations. In: 2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT); Kanpur, India, July 6-8, 2019. https://doi.org/10.1109/ICCCNT45670.2019

Cui, D. (2021). Image segmentation algorithm based on partial differential equation. Journal of Intelligent and Fuzzy Systems, 40(4):5945-5952. https://doi.org/10.3233/JIFS-189434

Getreuer, P. (2012). Rudin-osher-fatemi total variation denoising using split bregman. Image Processing on Line, 2:74-95. https://doi.org/10.5201/ipol.2012.g-tvd

Gonzalez, R.C., Woods, R.E., and Eddins, S.L. (2010). Digital Image ProcessingUsing MATLAB. 620p.

Ibrahim, R.W., Jalab, H.A., Karim, F.K., Alabdulkreem, E., and Ayub, M.N. (2022). A medical image enhancement based on generalized class of fractional partial differential equations. Quantitative Imaging in Medicine and Surgery, 12(1):172-183. https://doi.org/10.21037/qims-21-15

Mikula, K. (2002). Image processing with partial differential equations. In: Modern Methods in Scientific Computing and Applications. Bourlioux, A., Gander, M.J., and Sabidussi, G. (eds). NATO Science Series, Springer, Dordrecht, 175:283-321. https://doi.org/10.1007/978-94-010-0510-4_8

Perona, P. and Malik, J. (1990). Scale-space and edge detection using anisotropic diffusion. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12(7):629-639. https://doi.org/10.1109/34.56205

Pop, S., Lavialle, O., Terebes, R., Borda, M. (2007). A PDE-based approach for image fusion. In: Advanced Concepts for Intelligent Vision Systems. Blanc-Talon, J., Philips, W., Popescu, D., and Scheunders, P. (eds). ACIVS 2007. Lecture Notes in Computer Science, Springer, Berlin, Heidelberg, 4678:121-131. https://doi.org/10.1007/978-3-540-74607-2_11

Rajinikanth, V., Satapathy, S.C., Dey, N., and Vijayarajan, R. (2018). DWT-PCA Image Fusion Technique to Improve Segmentation Accuracy in Brain Tumor Analysis. In: Microelectronics, Electromagnetics and Telecommunications. Anguera, J., Satapathy, S., Bhateja, V., Sunitha, K. (eds). Lecture Notes in Electrical Engineering, Springer, Singapore, 471:453-462. https://doi.org/10.1007/978-981-10-7329-8_46

Rudin, L.I., Osher, S., and Fatemi, E. (1992). Nonlinear total variation based noise removal algorithms. Physica D: Nonlinear Phenomena, 60(1-4):259-268. https://doi.org/ 10.1016/0167-2789(92)90242-F

Trivedi, G.J. and Sanghvi, R. (2022a). Medical image fusion using cnn with automated pooling. Indian Journal of Science and Technology, 15(42):2267-2274. https://doi.org/ 10.17485/IJST/v15i42.1812

Trivedi, G.J. and Sanghvi, R. (2023b). Optimizing Image Fusion Using Modified Principal Component Analysis Algorithm and Adaptive Weighting Scheme, International Journal of Advanced Networking and Applications 15(1) : 5769-5774. 10.35444/IJANA.2023.1510

Trivedi, G.J. and Sanghvi, R. (2023c). Novel Approach to Multi-Modal Image Fusion using Modified Convolutional Layers. Journal of Innovative Image Processing, 5(3) : 229. https://doi.org/10.36548/jiip.2023.3.002

Trivedi, G.J. and Sanghvi, R. (2023c). Novel Approach to Multi-Modal Image Fusion using Modified Convolutional Layers. Journal of Innovative Image Processing, 5(3) : 229. https://doi.org/10.36548/jiip.2023.3.002

Trivedi, G.J., Shah, V., Sharma. J., and Sanghvi, R. (2023a). On solution of non-instantaneous impulsive Hilfer fractional integro-differential evolution system. Mathematica Applicanda,51(1):3-20. https://doi.org/10.14708/ma.v51i1.7167

Vanitha, K., Satyanarayana, D., and Prasad, M.N.G. (2019). A new hybrid medical image fusion method based on fourth-order partial differential equations decomposition and DCT in SWT domain. In: 2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT); Kanpur, India, 2019, p. 1-6. https://doi.org/10.1109/ICCCNT45670.2019

Xiao, G., Bavirisetti, D.P., Liu, G., and Zhang, X. (2020). Image Fusion. 1st ed. Springer Singapore, 404p. https://doi.org/ 10.1007/978-981-15-4867-3

You, Y.L. and Kaveh, M. (2000). Fourth-order partial differential equations for noise removal. IEEE Transactions on Image Processing, 9(10):1723-1730. https://doi.org/10.1109/ 83.869184

Zhang, Q. (2022). Construction of robot computer image segmentation model based on partial differential equation. Journal of Sensors, 2022:Article ID 6216423. https://doi.org/ 10.1155/2022/6216423

Downloads

Published

2023-11-17

How to Cite

Trivedi, G., & Sanghvi, R. (2023). A New Approach for Multimodal Medical Image Fusion using PDE-based Technique: A New Approach for Multimodal Medical Image Fusion using PDE-based Technique. Suranaree Journal of Science and Technology, 30(4), 030132(1–7). https://doi.org/10.55766/sujst-2023-04-e0843

Issue

Section

Short Article

Categories