Implementation and Comparative Study of Pyramid-based Image Fusion Techniques for Lumbar Spine Images
Received: 14 April 2023 | Revised: 2 May 2023 | Accepted: 10 May 2023 | Online: 10 June 2023
Corresponding author: Manan M. Nanavati
Abstract
Image fusion is a method of combining the necessary and relevant information from the set of source images into a single (fused) image which can be deemed to be more informative than the source. This paper discusses the implementation of various pyramid-based image fusion algorithms, such as the Laplacian pyramid, the ratio of the low-pass pyramid, the contrast pyramid, and the filter subtract decimate pyramid on multimodal CT and MR images of the lumbar spine. The fused images were evaluated using various objective evaluation quality metrics. The experimental results demonstrated that the ratio of the low pass pyramid achieved better performance compared to the other pyramids implemented, indicating that the fused image can also be used for further image fusion application or analysis purposes.
Keywords:
lumbar spine, medical image fusion, objective evaluation criteria, pyramid transformDownloads
References
R. Jha and T. Singh, "Multinomial logistic regression for breast thermogram classification," in 2017 International Conference on Communication and Signal Processing (ICCSP), Chennai, India, Apr. 2017, pp. 1266–1271.
H. K. Huang, "Biomedical image processing," Critical reviews in bioengineering, vol. 5, no. 3, pp. 185–271, Jan. 1981.
Y. Yang et al., "Multi-Focus Image Fusion via Clustering PCA Based Joint Dictionary Learning," IEEE Access, vol. 5, pp. 16985–16997, 2017.
H. M. El-Hoseny, W. Abd Elrahman, E. S. M. El. Rabaie, O. S. Faragallah, and F. E. Abd El-Sami, "Medical Image Fusion: A Literature Review Present Solutions and Future Directions," Menoufia Journal of Electronic Engineering Research, vol. 26, no. 2, pp. 321–350, Jul. 2017.
W. Kong, Y. Lei, and X. Ni, "Fusion technique for grey-scale visible light and infrared images based on non-subsampled contourlet transform and intensity–hue–saturation transform," IET Signal Processing, vol. 5, no. 1, pp. 75–80, Feb. 2011.
R. A. Mandhare, P. Upadhyay, and S. Gupta, "Pixel-Level Image Fusion Using Brovey Transforme and Wavelet Transform," International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, vol. 2, no. 6, Jun. 2013.
V. P. S. Naidu and J. R. Raol, "Pixel-level Image Fusion using Wavelets and Principal Component Analysis," Defence Science Journal, vol. 58, no. 3, Mar. 2008.
S. Li, X. Kang, L. Fang, J. Hu, and H. Yin, "Pixel-level image fusion: A survey of the state of the art," Information Fusion, vol. 33, pp. 100–112, Jan. 2017.
F. E. Z. A. El-Gamal, M. Elmogy, and A. Atwan, "Current trends in medical image registration and fusion," Egyptian Informatics Journal, vol. 17, no. 1, pp. 99–124, Mar. 2016.
A. P. James and B. V. Dasarathy, "Medical image fusion: A survey of the state of the art," Information Fusion, vol. 19, pp. 4–19, Sep. 2014.
S. Cheng, J. He, and Z. Lv, "Medical Image of PET/CT Weighted Fusion Based on Wavelet Transform," in 2008 2nd International Conference on Bioinformatics and Biomedical Engineering, Shanghai, China, Feb. 2008, pp. 2523–2525.
Q. Nawaz, B. Xiao, I. Hamid, and D. Jiao, "Multi-modal Color Medical Image Fusion Using Quaternion Discrete Fourier Transform," Sensing and Imaging, vol. 17, no. 1, Apr. 2016, Art. no. 7.
C. T. Kavitha, C. Chellamuthu, and R. Rajesh, "Medical Image Fusion using Combined Discrete Wavelet and Ripplet Transforms," Procedia Engineering, vol. 38, pp. 813–820, Jan. 2012.
M. Haddadpour, S. Daneshvar, and H. Seyedarabi, "PET and MRI image fusion based on combination of 2-D Hilbert transform and IHS method," Biomedical Journal, vol. 40, no. 4, pp. 219–225, Aug. 2017.
A. R. Doke, T. Singh, K. Shantanu, and R. Nayar, "Comparative analysis of wavelet transform methods for fusion of CT and PET images," in 2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI), Chennai, India, Sep. 2017, pp. 2152–2156.
Bhavana V. and Krishnappa H.K., "Multi-Modality Medical Image Fusion using Discrete Wavelet Transform," Procedia Computer Science, vol. 70, pp. 625–631, Jan. 2015.
Y. Na, L. Zhao, Y. Yang, and M. Ren, "Guided filter-based images fusion algorithm for CT and MRI medical images," IET Image Processing, vol. 12, no. 1, pp. 138–148, 2018.
R. Vadhi, V. S. Kilari, and S. S. Kumar, "An Image Fusion Technique Based on Hadamard Transform and HVS," Engineering, Technology & Applied Science Research, vol. 6, no. 4, pp. 1075–1079, Aug. 2016.
O. Prakash and A. Khare, "CT and MR Images Fusion Based on Stationary Wavelet Transform by Modulus Maxima," in Computational Vision and Robotics, New Delhi, India, 2015, pp. 199–204.
A. Gadge and D. S. S. Agrawal, "Guided Filter for Color Image," International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering, vol. 4, no. 6, pp. 250–252, Jun. 2016.
J. J. Lewis, R. J. O’Callaghan, S. G. Nikolov, D. R. Bull, and N. Canagarajah, "Pixel- and region-based image fusion with complex wavelets," Information Fusion, vol. 8, no. 2, pp. 119–130, Apr. 2007.
B. Zitová and J. Flusser, "Image registration methods: a survey," Image and Vision Computing, vol. 21, no. 11, pp. 977–1000, Oct. 2003.
H. Li, B. S. Manjunath, and S. K. Mitra, "Multisensor Image Fusion Using the Wavelet Transform," Graphical Models and Image Processing, vol. 57, no. 3, pp. 235–245, May 1995.
"Spineweb online database." http://spineweb.digitalimaginggroup.ca/.
R. Nair, T. Singh, and R. Nayar, "Logistic regression for Mouth (orotracheal) or Nose (nasotracheal) endotracheal intubation," in 2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI), Chennai, India, Sep. 2017, pp. 2026–2031.
C. S. Xydeas and V. Petrović, "Objective image fusion performance measure," Electronics Letters, vol. 36, no. 4, pp. 308–309, Feb. 2000.
S. Li, B. Yang, and J. Hu, "Performance comparison of different multi-resolution transforms for image fusion," Information Fusion, vol. 12, no. 2, pp. 74–84, Apr. 2011.
M. Hossny, S. Nahavandi, and D. Creighton, "Comments on ‘Information measure for performance of image fusion,’" Electronics Letters, vol. 44, no. 18, pp. 1066–1067, Aug. 2008.
N. Cvejic, C. Canagarajah, and D. Bull, "Image fusion metric based on mutual information and tsallis entropy," Electronics Letters, vol. 42, no. 11, pp. 626–627, May 2006, https://doi.org/10.1049/iel:20060693.
N. Behar and M. Shrivastava, "A Novel Model for Breast Cancer Detection and Classification," Engineering, Technology & Applied Science Research, vol. 12, no. 6, pp. 9496–9502, Dec. 2022.
N. Kumar, A. Hashmi, M. Gupta, and A. Kundu, "Automatic Diagnosis of Covid-19 Related Pneumonia from CXR and CT-Scan Images," Engineering, Technology & Applied Science Research, vol. 12, no. 1, pp. 7993–7997, Feb. 2022.
Downloads
How to Cite
License
Copyright (c) 2023 Manan M. Nanavati, Mehul Shah
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain the copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after its publication in ETASR with an acknowledgement of its initial publication in this journal.
