Edge detection of MRI brain images based on segmentation and classification using support vector machines and neural networks pattern recognition

Iourzikene, ZouhirBenazzouz, DjamelGougam, Fawzi2023-04-162023-04-162023978-303121215-423673370DOI 10.1007/978-3-031-21216-1_11https://link.springer.com/chapter/10.1007/978-3-031-21216-1_11https://dspace.univ-boumerdes.dz/handle/123456789/11320Brain tumor (brain cancer) is a mass of abnormal cells that grow in the brain in an uncontrolled way. Brain CT and brain MRI are the most frequently performed examinations. The objective of this paper is to develop a method for the classification of brain MRI images of healthy cases and tumor cases. MRI brain database is obtained by preprocessing, segmentation, feature extraction. Feature extraction based on support vector machines (clustering) is used in this research. The objective of this method is to create several vectors and each vector contains a number of features of each image, so that we can make the classification by these featuresenBrain imageNeural networks pattern recognitionSegmentationSupport vector machineEdge detection of MRI brain images based on segmentation and classification using support vector machines and neural networks pattern recognitionOther