Efficient Tumor Detection in MRI Brain Images
| Autor: | Manognya Katapally, Y. Sri Lalitha, Keerthana Pabba, Vineetha Mudunuri |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
medicine.diagnostic_test
business.industry Computer science Computer applications to medicine. Medical informatics General Engineering Brain tumor R858-859.7 Image processing Pattern recognition Magnetic resonance imaging Human brain medicine.disease Tumor detection medicine.anatomical_structure brain tumor mri image fuzzy clustering medicine Canny edge detector Segmentation Artificial intelligence Abnormality business |
| Zdroj: | International Journal of Online and Biomedical Engineering, Vol 16, Iss 13, Pp 122-131 (2020) |
| ISSN: | 2626-8493 |
| Popis: | Detection of brain of tumor is a laborious task as it involves identification, segmentation followed by detection of the tumor. It is a very challenging task to envisage uncommon structures in the image of human brain[15]. An Image processing concept called MRI can be used to visualize different structures of human body. The Magnetic Resonance images (MRI) are used to detect the uncommon portions of human brain. This paper explores different noise removal methods accompanied by Balance-contrast enhancement technique (BCET) which results in increased accuracy. Segmentation followed by canny edge detection is performed on the improved images to detect the fine edges of the abnormalities present. The model attained an accuracy of at most 98% in detecting the tumor or the abnormality in a human brain which determines the effectiveness of the proposed model. |
| Databáze: | OpenAIRE |
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