Advancements In Multi-Modality Medical Image Fusion: A Comprehensive Review

Authors

  • Anshita Kesharwani MTech Scholar, Department of Computer Science & Engineering, TIEIT, Bhopal, India
  • Kaptan Singh Associate Professor, Department of Computer Science & Engineering, TIEIT, Bhopal, India
  • Amit Saxena Associate Professor, Department of Computer Science & Engineering, TIEIT, Bhopal, India

Keywords:

Medical Image Fusion, DCT, DWT, PCA, Multimodality

Abstract

Multimodality medical image fusion involves the amalgamation of multiple images acquired through single or multiple imaging modalities. The purpose of medical image fusion methods is to enhance the quality of medical images by effectively capturing the key features within the fused output. This consequently enhances the practicality of medical images for diagnostic assessment and issue identification. Medical imaging modalities like magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET) have been developed and are extensively utilized for clinical diagnoses. These multimodality images harbor vital information crucial for precise and efficient diagnosis of brain ailments. As a result, amalgamating diverse image modalities in the medical domain to create a distinct image brimming with intricate anatomical details and heightened spectral information has become exceedingly valuable in clinical diagnosis. This manuscript offers an exhaustive examination of existing literature on image fusion, elucidating the fundamental concepts and materials essential for a comprehensive grasp of diverse medical fusion techniques.

References

Sumit Narayan Jarholiya, Dr. Shachi Awasthi,, “Multimodal Medical Image Fusion Using DC Coefficient Scaling and MWGF in DWT Domain” , International Journal of Research, 2021.

Sujoy Paul, Ioana S. Sevcenco and PanajotisAgathoklis. Image Fusion of multi focus and multi exposure by using Gradient Domain, University of California, 2016

XiangzhiBai, Miaoming Liu, Zhiguo Chen, Peng Wang, And Yu Zhang Gradient-domain Based Mathematical Morphology and Decision Map Construction for multi focus image fusion, Beijing University of Aeronautics and Astronautics, 2016.

PareshRawat, JyotiSinghai, “Image enhancement method for underwater, ground and satellite images using brightness preserving histogram equalization with maximum entropy”, IEEE international Conf. On Computational Intelligence and Multimedia Applications(ICCIMA) pp. 507-512. 2007.

Jayanta M., and Sanjit K. Mitra, “Enhancement of Colour Images by Scaling the DCT Coefficients”, IEEE Transactions on Image Processing, Vol. 17, No. 10, pp. 1783-1794, 2008

F. Huang, L. Zhang, Y. Zhou and X. Gao, "Adversarial and Isotropic Gradient Augmentation for Image Retrieval with Text Feedback," in IEEE Transactions on Multimedia, 2022, doi: 10.1109/TMM.2022.3222624.

G. Wang, W. Li, X. Gao, B. Xiao and J. Du, "Functional and Anatomical Image Fusion Based on Gradient Enhanced Decomposition Model," in IEEE Transactions on Instrumentation and Measurement, vol. 71, pp. 1-14, 2022, Art no. 2508714, doi: 10.1109/TIM.2022.3170983.

H. Vargas, J. Ramírez, S. Pinilla and J. I. Martínez Torre, "Multi-Sensor Image Feature Fusion via Subspace-Based Approach Using ell _{1}-Gradient Regularization," in IEEE Journal of Selected Topics in Signal Processing, vol. 17, no. 2, pp. 525-537, March 2023, doi: 10.1109/JSTSP.2022.3219357.

Gattim, N.K. & Rajesh, Vullanki&Partheepan, R. &Karunakaran, S. & Reddy, K.N. (2017). Multimodal image fusion using curvelet and genetic algorithm. Journal of Scientific and Industrial Research. 76. 694-696https://nopr.niscpr.res.in/bitstream/123456789/43038/1/JSIR%2076%2811%29%20694-696.pdf.

Xiaoxiao Li , XiaopengGuo , Student Member, IEEE, Pengfei Han ,Xiang Wang , Huaguang Li , and Tao Luo , “LaplacianRedecomposition for Multimodal Medical Image Fusion” , IEEE transactions on instrumentation and measurement, vol. 69, no. 9, september 2020 /

K. KoteswaraRao, K. Veera Swam. “Multimodal Medical Image Fusion using NSCT and DWT Fusion Frame Work” International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075 (Online), Volume-9 Issue-2, December 2019 DOI: 10.35940/ijitee.B8036.129219

Rajiv Singh and AshishKhare. “Multiscale Medical Image Fusion in Wavelet Domain”, Hindawi Publishing Corporation The Scientific World Journal Volume 2013, Article ID 521034, 10 pages http://dx.doi.org/10.1155/2013/521034

KapinaiahViswanath, Shweta , “ Enhancement of Brain Tumor Images “,2nd IEEE International Conference On Recent Trends in Electronics Information & Communication Technology (RTEICT), pp. 1894-1898, May 19-20, 2017

EhsanAmiri, Mina Rahmanian, SaeedAmiriand HadiYazdaniPraee, “Medical images fusion using two-stage combined model DWT and DCT”, International Advanced Researches and Engineering Journal 05(03): 344-351, 2021DOI: 10.35860/iarej.910982

Rakshitha.K, RashmiLaxmanGavadi, Akhilraj .V. Gadagkar , “Comparison of Different Methods for Fusion of Multimodal Medical Images”, International Research Journal of Engineering and Technology (IRJET) Volume: 04 Issue: 11 | Nov -2017”

Donia, E.A., El-Rabaie, ES.M., El-Samie, F.E.A. et al. Infrared image fusion for quality enhancement. J Opt 52, 658–664 (2023). https://doi.org/10.1007/s12596-022-01018-4

Seongbae Bang and Wonha Kim, “DCT Domain Detail Image Enhancement for More Resolved Images” ,Electronics 2021, 10, 2461. https://doi.org/10.3390/electronics10202461

V. Arya, H. Choubey, S. Sharma, T. -Y. Chen and C. -C. Lee, "Image Enhancement and Features Extraction of Electron Microscopic Images Using Sigmoid Function and 2D-DCT," in IEEE Access, vol. 10, pp. 76742-76751, 2022, doi: 10.1109/ACCESS.2022.3192416.

K. Kalaivani and Y. AsnathVictyPhamila, “Analysis of Image Fusion Techniques based on Quality Assessment Metrics”, Indian Journal of Science and Technology, Vol 9(31), DOI: 10.17485/ijst/2016/v9i31/92553, August 2016

Deron Rodrigues, Hasan Ali Virani, ShajahanKutty. Multimodal Image Fusion Techniques based on wavelets, Goa College of Engineering,2013.

Jarholiya, Sumit., Multimodal Medical Image Fusion Using DC Coefficient Scaling and MWGF in DWT Domain. International Journal of Research. 7. 01-11, 2021

Downloads

Published

2024-04-09

How to Cite

Kesharwani, A., Singh, K., & Saxena, A. (2024). Advancements In Multi-Modality Medical Image Fusion: A Comprehensive Review. International Journal of Innovative Research in Engineering and Management, 11(2), 55–61. Retrieved from http://ijirem.irpublications.org/index.php/ijirem/article/view/17