A comparison study: Classification brain tumor based on Support Vector Machine and K-Nearest Neighbors

Shler Farhad Khorshid and Nawzat Ahmed
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Shler Farhad Khorshid: Information Technology Department, Akre Technical College of Informatics, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq

International Journal of Science and Business, 2021, vol. 5, issue 6, 12-20

Abstract: Brain tumor is one of the commonest tumors. For the diagnosis of this disease, automated detection and classification are crucial. Magnetic resonance imaging (MRI) is a unique sort of imaging which is utilized for detecting these tumors and categorizing them as benign or malignant using special algorithms such as of K-Nearest Neighbors (K-NN) and Support Vector Machine (SVM). The classification of brain tumors through imaging can be divided into four phases: pre-processing, extraction, segmentation and classification. This paper reviews some recent studies that highlight the efficacy of K-NN and SVM accuracies in classifying brain MRI images as normal or abnormal, benign or malignant.

Keywords: brain tumor; Magnetic resonance imaging (MRI); classification; SVM; K-NN (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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