Detection of Brain Tumors Using Transfer Learning Features and Machine Learning Techniques

Detection of Brain Tumors Using Transfer Learning Features and Machine Learning Techniques
Author(s):
S. Sathishkumar, Janani, Kiruba, Harshitha, Dreghaa, Giftlin Priyanka
Keywords:
2D Magnetic Resonance brain Images (MRI), Convolutional Neural Network, Wiener filter, Fuzzy c-means.
Abstract
This paper proposes a Magnetic Resonance Imaging (MRI) based brain tumor image detection using ConvolutionalNeural Network (CNN) based deep learning method. In modern days, checking the huge number of MRI images and finding a brain tumor manually by a human is a very tedious and inaccurate task. It affects the proper medical treatment of the patient. Again, it is hugely time-consuming task as it involves a huge number of image datasets. The proposed an algorithm to segment brain tumors from 2D MRI by a convolutional neural network which is followed by traditional classifiers and deep learning methods and Transfer learning method for feature extraction. A CNN based model will help the doctors to detect brain tumors in MRI images accurately, so that the speed in treatment will increase a lot.
Article Details
Unique Paper ID: 158744 Publication Volume & Issue: Volume 9, Issue 10 Page(s): 632 - 635
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