R. Muthaiyan1,*, M. Malleswaran2
Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 891-907, 2022, DOI:10.32604/iasc.2022.024635
- 08 February 2022
Abstract Brain tumours are composed of cells where the growth is unrestrained. Though the incidence rate is lower, it is a serious threatening disease to human lives. For effective treatment, an accurate and quick method to classify Magnetic Resonance Imaging (MRI) is required. To identify the meaningful patterns and to interpret images, pattern recognition algorithms are developed. In this work, an extension of Shearlet transform named Bendlets is employed to interpret MRI images and decision making is done by ensemble learning using k-Nearest Neighbor (kNN), Naive Bayesian and Support Vector Machine (SVM) classifiers. The Bendlet and Ensemble More >
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