Abnormality Classification of Brain Tumor in MRI Images using Multiclass SVM
| Autor: | C. Saranya Jothi, Hijaj Mohammed, S. Alex David, V Usha |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Contextual image classification
Computer science business.industry Multiclass svm Brain tumor Pattern recognition medicine.disease Support vector machine Mri image medicine Medical imaging Pharmacology (medical) Artificial intelligence Abnormality business Pharmacology Toxicology and Pharmaceutics (miscellaneous) Classifier (UML) |
| Zdroj: | Research Journal of Pharmacy and Technology. 11:851 |
| ISSN: | 0974-360X 0974-3618 |
| DOI: | 10.5958/0974-360x.2018.00158.0 |
| Popis: | Automatic image classification is most important process in medical imaging for analyzing difference between normal patients and those who have the possibility of having abnormalities or tumor. MRI image consists of different gray levels and intensities. Brain tumor is varied in size and shape. Radiologist can diagnose and find location of lesions based on visual diagnosis with help of available software. While performing visual diagnosis, error may be introduced in finding location of tumor. To solve this problem there is need to develop a computer based automatic technique for detecting and classifying tumor from brain MRI images. The proposed system classifies the abnormalities in brain tumor by extracting the feature from brain tumor image and normal image using the GLCM and DWT. From the features classified by the classifier into two classes normal and abnormal along with different type of tumor by using the multiclass SVM which will give a promising result. |
| Databáze: | OpenAIRE |
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