Hybrid Convolutional Neuro-Fuzzy Networks for Diagnostics of MRI-Images of Brain Tumors

Author(s):  
Yuriy Zaychenko ◽  
Galib Hamidov
Keyword(s):  
2020 ◽  
Author(s):  
Samir Bandyopadhyay ◽  
Shawni Dutta

Abstract Life threatening diseases in both male and female are Brain tumor, stroke, hemorrhage and multiple sclerosis (MS). The most common and widespread disease among these brain diseases is Brain tumor. Early and accurate diagnosis of brain lesion is vital for determining accurate treatment and prognosis. However, the diagnosis is a very challenging task and can only be performed by specialists in neuroradiology. In this paper, initially MRI image is taken as input and is normalized. The second stage includes extraction of feature vectors from the image which results in reducing redundancy of data to serve as the input to the classifier. The classifier extracted vector as features to produce classified output. The methodology performed very efficiently and accurately. Proposed work exhibits the application of Fuzzy Inference System (FIS) based classifier known as Adaptive Neuro Fuzzy Inference System (ANFIS) to successfully classify the five major types of brain tumors.


1992 ◽  
Vol 3 (4) ◽  
pp. 781-789 ◽  
Author(s):  
J. Russell Geyer
Keyword(s):  

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