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Medical Image Fusion Algorithm based on Adaptive Selectivity Reconstruction and Pulse Coupled-Neural Network

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2020
Authors:
Mohamed El Aallaoui
10.5120/ijca2020920721

Mohamed El Aallaoui. Medical Image Fusion Algorithm based on Adaptive Selectivity Reconstruction and Pulse Coupled-Neural Network. International Journal of Computer Applications 175(19):1-9, September 2020. BibTeX

@article{10.5120/ijca2020920721,
	author = {Mohamed El Aallaoui},
	title = {Medical Image Fusion Algorithm based on Adaptive Selectivity Reconstruction and Pulse Coupled-Neural Network},
	journal = {International Journal of Computer Applications},
	issue_date = {September 2020},
	volume = {175},
	number = {19},
	month = {Sep},
	year = {2020},
	issn = {0975-8887},
	pages = {1-9},
	numpages = {9},
	url = {http://www.ijcaonline.org/archives/volume175/number19/31557-2020920721},
	doi = {10.5120/ijca2020920721},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

We propose a novel medical image fusion framework, based on adaptive selectivity reconstruction and pulse coupled-neural network. The proposed method takes advantage of the multiscale analysis and multiselectivity analysis, which enables it to capture the different structures information of different modality medical images. A subjective assessment comparing our method and other medical image fusion methodes is performed. Experiments showed that our method is more robust than the others, in both visual effect and objective evaluation criteria.

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Keywords

Continuous Wavelet Transform; Directional Wavelet; Angular Selectivity; Adaptive Selectivity; Medical Image Fusion