Tumor Detection and Classification of MRI Brain Image using Different Wavelet Transforms and Support Vector Machines
| Autor: | Mihaela Lascu, Dan Lascu, Mircea Gurbina |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Pathology
medicine.medical_specialty medicine.diagnostic_test business.industry Brain activity and meditation 05 social sciences 050209 industrial relations Wavelet transform Magnetic resonance imaging medicine.disease Support vector machine Tumor detection 0502 economics and business Medicine Sarcoma Mri brain business 050203 business & management Glioblastoma |
| Zdroj: | TSP |
| DOI: | 10.1109/tsp.2019.8769040 |
| Popis: | The brain is one of the most complex organs in the human body that works with billions of cells. A cerebral tumor occurs when there is an uncontrolled division of cells that form an abnormal group of cells around or within the brain. This cell group can affect the normal functioning of brain activity and can destroy healthy cells. Brain tumors are classified as benign or low-grade (grade 1 and 2) and malignant tumors or high-grade (grade 3 and 4). The proposed methodology aims to differentiate between normal brain and tumor brain (benign or malign). The study of some types of brain tumors such as metastatic bronchogenic carcinoma tumors, glioblastoma and sarcoma are performed using brain magnetic resonance imaging (MRI). The detection and classification of MRI brain tumors are implemented using different wavelet transforms and support vector machines. Accurate and automated classification of MRI brain images is extremely important for medical analysis and interpretation. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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