Review on multi-modality medical image fusion using deep learning

Research Article
Open access

Review on multi-modality medical image fusion using deep learning

Ishika Gupta 1 , Satyam Gupta 2 , Manoj Diwakar 3 , Prabhishek Singh 4 , Achyut Shankar 5 , Sathishkumar V E 6*
  • 1 Graphic Era Deemed to be University    
  • 2 Graphic Era Deemed to be University    
  • 3 Graphic Era Deemed to be University    
  • 4 Bennett University    
  • 5 University of Warwick    
  • 6 Jeonbuk National University    
  • *corresponding author sathish@jbnu.ac.kr
Published on 23 October 2023 | https://doi.org/10.54254/2755-2721/19/20231054
ACE Vol.19
ISSN (Print): 2755-273X
ISSN (Online): 2755-2721
ISBN (Print): 978-1-83558-029-5
ISBN (Online): 978-1-83558-030-1

Abstract

Multi-Modality medical image fusion is a method in which multiple images are merged having either single or multiple imaging modalities. This process is carried out to improve the quality of imaging while preserving all the essential and distinct features. Many areas such as Machine Learning, Artificial Intelligence, Image Processing, and Computer Vision are covered by Medical Image Fusion. This method has been adopted on a large scale by physicians to apprehend any damage or injury caused in organ tissues in clinical trials by performing a fusion of images with different modalities. In this review, Deep Learning methods carried out in the medical image fusion field have been discussed along with a comparison between their accuracies. The main objective of this paper is to list some of the most effective techniques in this domain and discuss their performance. At last, the paper concludes with the fact that although the development and growth in this area have increased over the years, many challenges have also come along the way.

Keywords:

multimodal, image fusion, neural network, deep learning, diagnosis, medical image

Gupta,I.;Gupta,S.;Diwakar,M.;Singh,P.;Shankar,A.;E,S.V. (2023). Review on multi-modality medical image fusion using deep learning. Applied and Computational Engineering,19,253-258.
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References

[1]. Singh, P., Diwakar, M., Cheng, X., & Shankar, A. (2021). A new wavelet-based multi-focus image fusion technique using method noise and anisotropic diffusion for real-time surveillance application. Journal of Real-Time Image Processing, 18(4), 1051-1068. doi:10.1007/s11554-021-01125-8.

[2]. Diwakar, M., Tripathi, A., Joshi, K., Sharma, A., Singh, P., Memoria, M., & Kumar, N. (2020). A comparative review: Medical image fusion using SWT and DWT. Materials Today: Proceedings, 37(Part 2), 3411-3416. doi:10.1016/j.matpr.2020.09.278.

[3]. Chakraborty, A., Jindal, M., Khosravi, M. R., Singh, P., Shankar, A., & Diwakar, M. (2021). A secure IoT-based cloud platform selection using entropy distance approach and fuzzy set theory. Wireless Communications and Mobile Computing, 2021 doi:10.1155/2021/6697467.

[4]. Dhaundiyal, R., Tripathi, A., Joshi, K., Diwakar, M., & Singh, P. (2020). Clustering based multi-modality medical image fusion. Paper presented at the Journal of Physics: Conference Series, , 1478(1) doi:10.1088/1742-6596/1478/1/012024.

[5]. Singh, P., & Diwakar, M. (2021). Wavelet-based multi-focus image fusion using average method noise diffusion (AMND). Recent Advances in Computer Science and Communications, 14(8), 2436-2448. doi:10.2174/2666255813999200720163938.

[6]. Diwakar, M., Singh, P., & Shankar, A. (2021). Multi-modal medical image fusion framework using co-occurrence filter and local extrema in NSST domain. Biomedical Signal Processing and Control, 68 doi:10.1016/j.bspc.2021.102788.

[7]. Singh, P., Diwakar, M., Chakraborty, A., Jindal, M., Tripathi, A., & Bajal, E. (2022). A non-conventional review on image fusion techniques. Paper presented at the 2021 IEEE 8th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering, UPCON 2021, doi:10.1109/UPCON52273.2021.9667653.

[8]. Diwakar, M., Singh, P., Shankar, A., Nayak, S. R., Nayak, J., Vimal, S.,Sisodia, D. (2022). Directive clustering contrast-based multi-modality medical image fusion for smart healthcare system. Network Modeling Analysis in Health Informatics and Bioinformatics, 11(1) doi:10.1007/s13721-021-00342-2.

[9]. Singh, P., Shankar, A., Diwakar, M., & Khosravi, M. R. (2022). MSPB: Intelligent SAR despeckling using wavelet thresholding and bilateral filter for big visual radar data restoration and provisioning quality of experience in real-time remote sensing. Environment, Development and Sustainability, doi:10.1007/s10668-022-02395-3.

[10]. Singh, P., Shankar, A., & Diwakar, M. (2022). Review on nontraditional perspectives of synthetic aperture radar image despeckling. Journal of Electronic Imaging, 32(2), 021609.

[11]. Bing Huang, Feng Yang, Mengxiao Yin, Xiaoying Mo, Cheng Zhong, "A Review of Multimodal Medical Image Fusion Techniques", Computational and Mathematical Methods in Medicine, vol. 2020, Article ID 8279342, 16 pages, 2020.

[12]. Chanumolu, Rahul, Likhita Alla, Pavankumar Chirala, Naveen Chand Chennampalli, and Bhanu Prakash Kolla. "Multimodal Medical Imaging Using Modern Deep Learning Approaches." In 2022 IEEE VLSI Device Circuit and System (VLSI DCS), pp.184-187. IEEE, 2022.

Cite this article

Gupta,I.;Gupta,S.;Diwakar,M.;Singh,P.;Shankar,A.;E,S.V. (2023). Review on multi-modality medical image fusion using deep learning. Applied and Computational Engineering,19,253-258.

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The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 5th International Conference on Computing and Data Science

ISBN：978-1-83558-029-5(Print) / 978-1-83558-030-1(Online)
Editor：Roman Bauer, Marwan Omar, Alan Wang
Conference website: https://2023.confcds.org/
Conference date: 14 July 2023
Series: Applied and Computational Engineering
Volume number: Vol.19
ISSN：2755-2721(Print) / 2755-273X(Online)

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References

[1]. Singh, P., Diwakar, M., Cheng, X., & Shankar, A. (2021). A new wavelet-based multi-focus image fusion technique using method noise and anisotropic diffusion for real-time surveillance application. Journal of Real-Time Image Processing, 18(4), 1051-1068. doi:10.1007/s11554-021-01125-8.

[2]. Diwakar, M., Tripathi, A., Joshi, K., Sharma, A., Singh, P., Memoria, M., & Kumar, N. (2020). A comparative review: Medical image fusion using SWT and DWT. Materials Today: Proceedings, 37(Part 2), 3411-3416. doi:10.1016/j.matpr.2020.09.278.

[3]. Chakraborty, A., Jindal, M., Khosravi, M. R., Singh, P., Shankar, A., & Diwakar, M. (2021). A secure IoT-based cloud platform selection using entropy distance approach and fuzzy set theory. Wireless Communications and Mobile Computing, 2021 doi:10.1155/2021/6697467.

[4]. Dhaundiyal, R., Tripathi, A., Joshi, K., Diwakar, M., & Singh, P. (2020). Clustering based multi-modality medical image fusion. Paper presented at the Journal of Physics: Conference Series, , 1478(1) doi:10.1088/1742-6596/1478/1/012024.

[5]. Singh, P., & Diwakar, M. (2021). Wavelet-based multi-focus image fusion using average method noise diffusion (AMND). Recent Advances in Computer Science and Communications, 14(8), 2436-2448. doi:10.2174/2666255813999200720163938.

[6]. Diwakar, M., Singh, P., & Shankar, A. (2021). Multi-modal medical image fusion framework using co-occurrence filter and local extrema in NSST domain. Biomedical Signal Processing and Control, 68 doi:10.1016/j.bspc.2021.102788.

[7]. Singh, P., Diwakar, M., Chakraborty, A., Jindal, M., Tripathi, A., & Bajal, E. (2022). A non-conventional review on image fusion techniques. Paper presented at the 2021 IEEE 8th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering, UPCON 2021, doi:10.1109/UPCON52273.2021.9667653.

[8]. Diwakar, M., Singh, P., Shankar, A., Nayak, S. R., Nayak, J., Vimal, S.,Sisodia, D. (2022). Directive clustering contrast-based multi-modality medical image fusion for smart healthcare system. Network Modeling Analysis in Health Informatics and Bioinformatics, 11(1) doi:10.1007/s13721-021-00342-2.

[9]. Singh, P., Shankar, A., Diwakar, M., & Khosravi, M. R. (2022). MSPB: Intelligent SAR despeckling using wavelet thresholding and bilateral filter for big visual radar data restoration and provisioning quality of experience in real-time remote sensing. Environment, Development and Sustainability, doi:10.1007/s10668-022-02395-3.

[10]. Singh, P., Shankar, A., & Diwakar, M. (2022). Review on nontraditional perspectives of synthetic aperture radar image despeckling. Journal of Electronic Imaging, 32(2), 021609.

[11]. Bing Huang, Feng Yang, Mengxiao Yin, Xiaoying Mo, Cheng Zhong, "A Review of Multimodal Medical Image Fusion Techniques", Computational and Mathematical Methods in Medicine, vol. 2020, Article ID 8279342, 16 pages, 2020.

[12]. Chanumolu, Rahul, Likhita Alla, Pavankumar Chirala, Naveen Chand Chennampalli, and Bhanu Prakash Kolla. "Multimodal Medical Imaging Using Modern Deep Learning Approaches." In 2022 IEEE VLSI Device Circuit and System (VLSI DCS), pp.184-187. IEEE, 2022.

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