69
Views
0
CrossRef citations to date
0
Altmetric
Research Articles

Multimodal medical image fusion using residual network 50 in non subsampled contourlet transform

&
Pages 677-690 | Received 08 Nov 2022, Accepted 26 Jan 2023, Published online: 20 Jun 2023

References

  • James AP, Dasarathy BV. Medical image fusion: A survey of the state of the art. Inf Fusion. 2014;19:4–19. doi:10.1016/j.inffus.2013.12.002.
  • Du J, Li W, Lu K, et al. An overview of multi-modal medical image fusion. Neurocomputing. 2016;215:3–20. doi:10.1016/j.neucom.2015.07.160.
  • Wang Z, Ma Y. Medical image fusion using m-PCNN. Inf Fusion. 2008;9:176–185.
  • Wang Z, Li X, Duan H, et al. Medical image fusion based on convolutional neural networks and non-subsampled contourlet transform. Expert Syst Appl. 2021;171:114–124.
  • Yang Y, Que Y, Huang S, et al. Multiple visual features measurement With gradient domain guided filtering for multisensor image fusion. IEEE Trans Instrum Meas. 2017;66(4):691–703.
  • Zhao W, Lu H. Medical image fusion and denoising with alternating sequential filter and adaptive fractional order total variation. IEEE Trans Instrum Meas. 2017;66(9):2283–2294.
  • Li S, Kang X, Hu J. Image fusion with guided filtering. IEEE Trans Image Process. 2013;22(7):2864–2875.
  • EG K, Tirupal T. Performance of image fusion techniques for satellite images. Int J Tech Res Eng. 2015;2(12):3184–3194.
  • Li H, Manjunath BS, SK M. Multisensor image fusion using the wavelet transform. Graph Models Image Process. 1995;57(3):235–245.
  • Lewis JJ, O’Callaghan RJ, Nikolov SG, et al. Pixel- and region-based image fusion with complex wavelets. Inf Fusion. 2007;8(2):119–130.
  • Zhang Q, Guo B-L. Multifocus image fusion using the nonsubsampled contourlet transform. Signal Process. 2009;89(7):1334–1346.
  • Guorong G, Luping X, Dongzhu F. Multi-focus image fusion based on non-subsampled shearlet transform. IET Image Process. 2013;7(6):633–639.
  • Tan W, Tiwari P, Pandey HM. Multi-modal medical image fusion algorithm in the era of big data. Neural Comput Applic. 2020.
  • Wang L, Li B, Tian L. Multimodal medical volumetric data fusion using 3-D discrete shearlet transform and global-to-local rule. IEEE Trans Biomed Eng. 2014;61(1):197–206.
  • Qu X-B, Yan J-W, Xiao H-Z, et al. Image fusion algorithm based on spatial frequency-motivated pulse coupled neural networks in nonsubsampled contourlet transform domain. Acta Autom Sin. 2008;34(12):1508–1514.
  • Bhatnagar G, Wu QMJ, Liu Z. Directive contrast based multimodal medical image fusion in NSCT domain. IEEE Trans Multimedia. 2013;15(5):1014–1024.
  • Tann W, Xiang P, Thiton W. Multi-modal brain image fusion based on multi-level edge-preserving filtering. Biomed Signal Process Control. 2021;64:102280.
  • Liu Z, Yin H, Chai Y, et al. A novel approach for multimodal medical image fusion. Expert Syst Appl. 2014;41(16):7425–7435.
  • Rao KK, swamy KV. Multimoda medical image fusion using Laplacian Re-decomposition. Mater Sci Eng. 2021: 1070012080.
  • Du J, Li W, Xiao B, et al. Union Laplacian pyramid with multiple features for medical image fusion. Neurocomputing. 2016;194:326–339.
  • Yang Y, Que Y, Huang S, et al. Multimodal sensor medical image fusion based on type-2 fuzzy logic in NSCT domain. IEEE Sensors J. 2016;16(10):3735–3745.
  • Zhu Z, Yin H, Chai Y, et al. A novel multi-modality image fusion method based on image decomposition and sparse representation. Inf Sci. 2018;432:516–529.
  • Liu Y, Chen X, Cheng J, et al. A medical image fusion method based on convolutional neural networks. in Proc. 20th Int. Conf. Inf. Fusion. 2017: 1–7.
  • Liu Y, Peng CX, Wang H, et al. Multi-focus image fusion with a deep convolutional neural network. Inf Fusion. 2017;36:191–207.
  • Eckhorn R. Feature linking via synchronization among distributed assemblies: simulations of results from Cat visual cortex. Neural Comput. 1990;2(3):293–307.
  • Szu H, Kopriva I, Hoekstra P. Early tumor detection by multiple infrared unsupervised neural nets fusion. Proc of IEEE 25th Annual Int Conf on Engineering in Med Biol Soc. 2004: 1133–1145.
  • Zhang Q, Liang M, Sun W. Medical diagnostic image fusion based on feature mapping wavelet neural networks. Proc of IEEE 3rd Int Conf on Image and Graphics. 2004: 51–54. doi:10.1109/ICIG.2004.93.
  • Xiaoqi L, Baohua Z, Yong G. Medical image fusion algorithm based on clustering neural network. IEEE 1st Int Conf Bioinform Biomed Eng. 2007: 637–650.
  • Kong W, Miao Q, Lei Y. Multimodal sensor medical image fusion based on local difference in non-subsampled domain. IEEE Xplore. 2018;68(4).
  • Bhuvaneswari C, Aruna P, Loganathan D. A new fusion model for classification of the lung diseases using genetic algorithm. Egypt Inform J. 2014;15:69–77. doi:10.1016/j.eij.2014.05.001.
  • Rao KK, Swamy KV. Multimodal medical image fusion based on NSCT and DWT fusion framework. IJITEE. 2019;9(2).
  • Rao KK, Swamy KV. Multimodal medical image fusion with Butterworth filter in NSCT domain based on dual fusion framework. IJAST. 2020;29(8):1363–1375.
  • Panigrahy C, Seal A, Mahato NK. Mri and SPECT image fusion using a weighted parameter adaptive dual channel PCNN. IEEE Signal Process Lett. 2020;27:690–694.
  • Sengupta A, Seal A, Panigrahy C, et al. Edge information based image fusion metrics using fractional order differentiation and sigmoidal functions. IEEE Access. 2020;8:88385–88398.
  • Seal A, Bhattacharjee D, Nasipuri M, et al. PET-CT image fusion using random forest and à-trous wavelet transform. Int J Numer Method Biomed Eng. 2018;34(3).
  • Cunha. The nonsubsampled contourlet transform: theory, design, and applications. IEEE Trans Image Process. 2006;15(10):3089–3101.
  • Liu Y, Chen X, RK W, et al. Image fusion with convolutional sparse representation. IEEE Signal Process Lett. 2016;23(12):1882–1886.
  • Hossny M, Nahavandi S, Creighton D, et al. Image fusion performance metric based on mutual information and entropy driven quadtree decomposition. Electron Lett. 2010;46(18):1266–1268.
  • Sarwinda D, Paradisa RH, Bustamam A, et al. Deep learning in image classification using residual network (ResNet) variants for detection of colorectal cancer, 5th international conference on computer science and computational intelligence 2020, procedia comput. Sci. 2021;179:423–431.
  • Fu J, Li W, Peng X, et al. A multiscale dense residual attention network for magnetic resonance and nuclear medicine image fusion, Biomed. Signal Process Control. 2023;80(2):104–118.
  • Easley G, Labate D, Lim W-Q. Sparse directional image representations using the discrete shearlet transform. Appl Comput Harmon Anal. 2008;25(1):25–46.
  • Zhu Z, Zheng M, Wang D, et al. A phase congruency and local Laplacian energy based multi-modality medical image fusion method in NSCT; 2019.
  • Dinh P-H. Combining spectral total variation with dynamic threshold neural P systems for medical image fusion, Biomed. Signal Process Control. 2023;80(2):104–114.
  • Chen Y, Park SK, Ma Y, et al. A new automatic parameter setting method of a simplified PCNN for image segmentation. IEEE Trans Neural Netw. 2011;22(6):880–89.
  • Zhan K, Shi J, Wang H, et al. Computational mechanisms of pulse-coupled neural networks: A comprehensive review. Arch Comput Methods Eng. 2017;24:573–588.
  • Li L, Ma H. Pulse coupled neural network-based multimodal medical image fusion via guided filtering and WSEML in NSCT domain. Entropy. 2021;23(5):591.
  • http://www.med.harvard.edu/AANLIB
  • Liu Y, Chen X, Ward RK, et al. Medical image fusion via convolutional sparsity based morphological component analysis. IEEE Signal Process Lett. 2019;26(3):485–489.
  • Du J, Li W, Xiao B. Anatomical-functional image fusion by information of interest in local Laplacian filtering domain. IEEE Trans Image Process. 2017;26(12):5855–5866.
  • Yang B, Li S. Multifocus image fusion and restoration With sparse representation. IEEE Trans Instrum Meas. 2010;59(4):884–892.
  • Das K. A neuro-fuzzy approach for medical image fusion. IEEE Trans Biomed Eng. 2013;60(12):3347–3353.
  • Yin L, Chen X. Medical image fusion with parameter-adaptive pulse coupled neural network in nonsubsampled shearlet transform domain. IEEE Trans Instrum Meas. 2019;68(1):49–64.
  • Du J, Li W, Xiao B. Fusion of anatomical and functional images using parallel saliency features. Inf Sci. 2018;430:567–576.
  • Li W, Zhang Y, Wang G, Huang Y, and Li R. A dual-branch feature enhanced network integrating transforms and convolutional feature learning for multimodal medical image fusion, Biomed Signal Process Control, 2023; 80(2).

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.