A Comparative analysis of MRI Brain Tumor by Using PNN Technique
Keywords:
Gray- level co-occurrence matrix (GLCM), Principal Component Analysis method (PCA), probabilistic neural network (PNN), Brain tumorAbstract
In the present world, brain tumor is becoming main
reason of causing death all over the world. Brain
tumor is causing due to the collection of abnormal
cells inside mind. So, the detection of these
abnormal cells is very complex due to their cell
formation. It is very important to classified type of
tumor like normal, benign, malignant. Brain tumor
is detected by MRI images. The probabilistic
neural network NN is used to classify the stages of
mind tumor automatically. In this research study is
suggested approach in the classification of brain
tumor. This work focuses primarily on two key
aspects of the classification problems viz. data preprocessing that is raw by using the networks. A
Probabilistic Neural network (PNN) has been very
useful in the categorization of new data sets. The
working of PNN are based upon the Baye’s
theorem which are considering the values of
features of classified data as true and then
predicting the classification of any new picture
basis on it. The values of feature of the twelve
enlisted features serve as educating the data of
neural network NN.
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