Open AccessDetection and Classification of Brain LesionDepending on Statistical Features Textural Analysis
Author(s) -
Alaa Noori Mazher,
Maysaa R. Naeemah,
Alyaa H. Ali
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1660/1/012050
Subject(s) - lesion , support vector machine , brain hemorrhage , artificial intelligence , pattern recognition (psychology) , ischemic stroke , medicine , computer science , radiology , pathology , ischemia , blood pressure
The early detection of brain lesion which includes the stroke (Hemorrhage and Ischemic) and cancer helps the doctors to overcome the health problem in the future. The correct diagnose may save many people from death. the medical image processing including the supervised classification “support vector machine”, “the gray level neighbors matrix”, “Fisher’s Discrimination Ratio(FDR)” and the Accuracy matrix to detect and classify the brain lesion, twenty twocomputed tomography (CT) brain images have been taken with size 512×512. This methods provides very good diagnosis of the brain lesion, the accuracy for cancer detection is 98%, for the Hemorrhage is 96%, for the ischemic 99% and normal 90%.