A Novel Approach of Medical Image Fusion using Wavelet Transforms
Image processing applications have been growing rapidly in real world. The term fusion means an approach to extract the useful information from several modalities. Image fusion (IF) is used to integrate the complementary information obtained from multisensor, multiview and/or multitemporal and get an image of more information and the quality of which cannot be achieved from any individual image. Different fusion algorithms are useful in many applications like medical diagnosis of CT, MRI and/or PET images. Particularly in brain medical imaging, fusing various modalities like MRI and CT images into a single image with in depth anatomical information and high spectral information is needed in clinical diagnosis. This process not only helps for better diagnosis, it also helps to reduce the storage space of medical images. Image fusion can be possible at three different levels viz., pixel level, feature level and decision level. This paper discusses pixel level based fusion algorithms like Averaging fusion, Discrete Wavelet Transform (DWT) based averaging fusion and DWT maximum approximation algorithms. The algorithms are implemented using LabView and simulation results are obtained for various fusion techniques applied on two different data sets of MRI and CT scan images were compared using the quality assessment parameters Mean Squared Error(MSE), Peak Signal to Noise Ratio (PSNR), Entropy and Structural Similarity Index (SSIM). It is observed that DWT maximum approximation fusion technique yields better result compared to other implemented algorithms.
Surya Prasada Rao Borra, Rajesh K Panakala and P.Rajesh Kumar, “Hybrid Image Fusion Algorithm using DWT Maximum Selection Rule and PCA,Internsational Journal of Scientific and Engineering Research, Volume8 , Isuue 8, August 2017, pp. 814-820.
Nemir Al-Azzawi and Wan Ahmed K. Wan Abdullah. “Medical Image Fusion Schemes using Contourlet Transform and PCA Based”, Biomedical Electronics group, Universiti Sains Malaysia(Article)
Aishwarya N, Abirami S and Amutha R, “Multifocus Image Fusion Using Discrete Wavelet Transform And Sparse Representation”, IEEE WiSPNET 2016 conference, pp. 2377-2382.
B.surya Prasada Rao, Rajesh K Panakala and P.Rajesh Kumar, “An Exposure towards performance of Image Fusion Strategies” International Conference on innovations in information, Embedded and Communication Systems (ICIIECS- 2016), pp. 451-454.
M.D. Nandeesh and Dr.M. Meenakshi, “Image Fusion Algorithms for Medical Images-A Comparison’, Bonfring International Journal of Advances in Image Processing, Vol. 5, No. 3, July 2015, pp. 23-26.
Dr. Deepali Sale, Swati Sawant, “Wavelet Based selection for fusion of Medical images”,
B.surya Prasada Rao, Rajesh K Panakala and P.Rajesh Kumar, “Contrast Enhancementof Low Dose CT Scan Images”, International Journal of Control Theory and Applications, 8(5), 2015, pp. 2415-2422 © International Science Press.
Lukka Sirisha, A.Geetha Devi and B. Surya Prasada Rao, “An Effective Method of Denoising of 2-D Data Using Adaptive Kernel Bilateral Filter”, International Journal of Scientific & Engineering Research, Volume 7, Issue 11, November-2016, pp. 565-571.
Bhavana. V and Krishnappa. H.K, “Fusion of MRI and PET Images using DWT and Adaptive Histogram Equalization”, International Conference on communication and Signal Processing, April 6-8, 2016, India, pp. 795-798.
Wencheng Wang, Faliang Chang,” A Multi-focus Image Fusion Method Based on Laplacian Pyramid”, journal of computers, vol.6, no. 12, december 2011.
Tapasmini Sahoo, Sankalp Mohanty and Saurav Sahu,” Multi-Focus Image Fusion Using Variance Based Spatial Domain and Wavelet Transform” International Conference on Multimedia, Signal Processing and Communication Technologies, 978-1-4577-1107-7.IEEE 2011.
G. S., M. Z. Kurian and H. N. Suma, "Fusion of CT and PET Medical Images Using Hybrid Algorithm DWT- DCT-PCA," 2015 2nd International Conference on Information Science and Security (ICISS), Seoul, 2015, pp. 1-5.
J. M. Headlee, E. J. Balster and W. F. Turri, "A no-reference image enhancement quality metric and fusion technique," 2015 International Conference on Image and Vision Computing New Zealand (IVCNZ), Auckland, 2015, pp. 1-6.
A. S. Sekhar and M. N. G. Prasad, "A novel approach of image fusion on MR and CT images using wavelet trans forms ," 2011 3rd International Conference on Electron ics Computer Technology, Kanyakumari, 2011, pp. 172-176
L. Wang, J. Du, S. Zhu, D. Fan and J. Lee, "New region- based image fusion scheme using the discrete wavelet frame transform," 2016 12th World Congress on Intelligent Control and Automation (WCICA), Guilin, 2016, pp. 3066- 3070.
- There are currently no refbacks.
This site has been shifted to https://stmcomputers.stmjournals.com/