Brain Tumor Classification Using Shape Analysis of MRI Images

8 Pages Posted: 25 Jul 2019 Last revised: 30 Sep 2019

See all articles by Bhagyashri Asodekar

Bhagyashri Asodekar

PCCOE, Pune(411044)-India

Prof. Sonal Gore

PCCOE, Pune(411044)-India

Date Written: May 18, 2019

Abstract

Brain tumor is mass of normal and abnormal cells in a brain. In medical field, MRI images are widely used for brain tumor detection. MRI images gives broad information about soft tissues of human body. This information can be used for brain tumor detection by using feature extraction technique. Brain tumor can be classified into Benign and Malignant. The common goal of feature extraction and representation techniques is to convert the segmented objects into representations that better describe their main features and attributes. The proposed methodology describes extraction of tumor from MRI images. Firstly, find out the region of interest of brain tumor for feature extraction and then calculate the shape features. Obtained shape features used for the classification of Benign and Malignant tumor. Random forest gives the better accuracy than support vector machine for classification of tumor.

Keywords: Classification, MRI images, Segmentation, Shape features

JEL Classification: Y60

Suggested Citation

Asodekar, Bhagyashri and Gore, Prof. Sonal, Brain Tumor Classification Using Shape Analysis of MRI Images (May 18, 2019). Proceedings of International Conference on Communication and Information Processing (ICCIP) 2019, Available at SSRN: https://ssrn.com/abstract=3425335 or http://dx.doi.org/10.2139/ssrn.3425335

Bhagyashri Asodekar (Contact Author)

PCCOE, Pune(411044)-India ( email )

Prof. Sonal Gore

PCCOE, Pune(411044)-India ( email )

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