Identifying Brain Tumour from Brain MRI images by ensemble learning methods

• Published in: 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT) pp. 1 - 5
• Main Authors: Doke, Ashwini, Rao K P, Vyshali
• Format: Conference Proceeding
• Language: English
• Published: IEEE 06-07-2023
• Subjects: Decision trees; ensemble learning methods; Gabor filters; Image classification; Learning systems; Machine learning; Magnetic resonance imaging; Medical services; Naive Bayes methods; Support vector machines
• ISSN: 2473-7674
• DOI: 10.1109/ICCCNT56998.2023.10306865

Brain Tumour is nothing but abnormal Growth of cell in brain which can be detected using Brain MRI and finding the information about uncontrolled growth of cell in Brain. The present research talk about detecting the Brain tumour by first transforming and MRI image into different forms using Gabor filters and then identifying an important features from them And finally by Appling different ensemble learning methods namely Decision Tree, SVM, KNN, Naive Bayes , SGD, to identify is tumour exists or not, Our results show significant differences and we can say that SVM has highest performance among KNN, Decision Tree, Naive bayes classifiers whereas SGD performs very less.so to classify the Brain MRI Images we can say SVM is the best classifier. Which will be significantly useful for Doctors and Medical practitioners to take quick decision in order to identify Brain tumour.