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

S. Sathishkumar; Janani; Kiruba; Harshitha; Dreghaa; Giftlin Priyanka

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

Authors: S. Sathishkumar, Janani, Kiruba, Harshitha, Dreghaa, Giftlin Priyanka

Unique Paper ID: 158744
Volume: 9
Issue: 10
PageNo: 632-635

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.

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Cite This Article

ISSN: 2349-6002
Volume: 9
Issue: 10
PageNo: 632-635

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

Available:https://ijirt.org/Article?manuscript=158744

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Journal no 47859

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