Implementation of Medical Image Fusion using Neuro-Fuzzy Logic
|International Journal of Electronics and Communication Engineering|
|© 2018 by SSRG - IJECE Journal|
|Volume 5 Issue 7|
|Year of Publication : 2018|
|Authors : Mr.Phapale Harish Anil and Prof.Bansode Rahul Sitaram|
How to Cite?
Mr.Phapale Harish Anil and Prof.Bansode Rahul Sitaram, "Implementation of Medical Image Fusion using Neuro-Fuzzy Logic," SSRG International Journal of Electronics and Communication Engineering, vol. 5, no. 7, pp. 1-6, 2018. Crossref, https://doi.org/10.14445/23488549/IJECE-V5I7P101
This paper gets a handle on medical image fusion (MIF) problems. These problems are simply known as image fusion problems.We can use RPCNN(Reduced Pulse coupled neural network)to provide better performance .The RPCNN linking dependents on fuzzy membership values. This value serves their significance in the analogous source image. The RPCNN has less complex structurekey advantage of such structure is that RPCNN require less number of parameters. The less complex structure and less parameter improve computational efficiency. This computational efficiency is important requirement of point-of-care (POC) health care technologies. The proposed scheme is free from the trivial defalcation of the modernization of MIF techniques: contrast reduction, loss of image fine details and unwanted image degradations etc.
Artificial neural network, fuzzy logic, image analysis,image fusion (IF), medical imaging (MI).
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