Brain Tumor Detection Using an Artificial Neural Network in MRI Images

Authors

  • Sruthy V Department of Electronics and Communication L B S College of Engineering, Kasaragod Kerala, India
  • Dr. Arathi T Department of Electronics and Communication L B S College of Engineering, Kasaragod Kerala, India

DOI:

https://doi.org/10.37591/(rrjobi).v5i1.184

Keywords:

Brain tumor, brain tumor detection, artificial neural networks, magnetic resonance imaging

Abstract

MRI is the widely used imaging technique in the biomedical field for the detection, diagnosis and evaluation of brain tumors. The large structural variability among brain tumor makes detection of a challenging problem. The medical problems are severe, if the tumor is detected at the later stage. Hence, diagnosis is necessary at the earliest. In this work, a neural network classifier is used for the detection of tumors from the brain MRI images. The classification involves labeling the images into normal and abnormal (tumor detected). The work incorporates steps for preprocessing, feature extraction and classification using neural network techniques. Texture features and moment features are extracted from the image and are used to train the artificial neural network and classify brain tumor. The system significantly improves the classification accuracy of brain tumor detection.

 

Keywords: Brain tumor, brain tumor detection, artificial neural networks, magnetic resonance imaging

 

Cite this Article

Sruthy V, Arathi T. Brain Tumor Detection Using an Artificial Neural Network in MRI Images. Research & Reviews: A Journal of Bioinformatics. 2018; 5(1): 14–22p.

 

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Published

2018-07-23

Issue

Vol. 5 No. 1 (2018)

Section

Research Article

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