Abstract
MRI is a progressive imaging system in medical field utilized to make best digital scan images of the internal parts enclosed in the human body. MRIs generate more detailed scan images than CT scans and are the favored way to identify a brain tumor. A brain tumor is defined as the growth of unusual cells in the tissues of the brain, which can be benign/ noncancerous or malignant/cancerous. It signifies a fascinating method for the structural valuation of tumors in brain since also offers high resolution data as well as greater soft tissue contrast. In this research, MRI scan images are taken for process further. So, in this research, the various machine learning techniques utilized for brain tumor detection such as SVM, KNN, NB and ensemble are analyzed. Hence, all these classification techniques are examined for finest results also reach maximum accuracy.
Cite
CITATION STYLE
Kavipriya, P. (2020). Performance Analysis and Comparison of Machine Learning Algorithms for Classification of Brain Tumor in MRI Images. Bioscience Biotechnology Research Communications, 13(13), 159–164. https://doi.org/10.21786/bbrc/13.13/22
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