| Autor: |
D., Rajath, H. S., Rajendra Prasad, Jairam, Bhat Geetalaxmi, N. I., Suhas, Karthik, U. |
| Předmět: |
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| Zdroj: |
Grenze International Journal of Engineering & Technology (GIJET); Jun2024, Vol. 10 Issue 2, Part 2, p1241-1248, 8p |
| Abstrakt: |
The computerized examination of brain tumors is critical in the early and correct diagnosis of neurological illnesses. This study proposes a new approach that combines image processing techniques and machine learning algorithms for the automatic detection and categorization of brain tumors in medical pictures. The proposed system uses advanced image processing algorithms to enhance and preprocess magnetic resonance imaging (MRI) scans of the brain. Preprocessing processes include noise reduction, contrast enhancement, and segmentation to extract the regions of interest. Following that, a feature extraction procedure is used to extract significant features from the preprocessed pictures, collecting key properties indicative of tumor existence and type. During the machine learning phase, a robust classification model is trained on a broad collection of annotated brain images. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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