Article
BRAIN TUMOR DETECTION USING IMAGE PROCESSING
Brain tumor detection is a critical task in the field of medical imaging, as early diagnosis can significantly improve patient survival rates. Magnetic Resonance Imaging (MRI) is widely used for identifying brain abnormalities due to its highresolution imaging capability. However, manual analysis of MRI scans is timeconsuming and may lead to human errors. This project presents an automated approach for brain tumor detection using image processing techniques. The proposed system involves preprocessing of MRI images to remove noise and enhance quality, followed by segmentation methods such as thresholding and clustering to isolate the tumor region. Morphological operations are applied to refine the detected area, and feature extraction techniques are used to analyze the size and shape of the tumor. The system is implemented using MATLAB, providing efficient processing and visualization tools. The results demonstrate accurate detection and clear identification of tumor boundaries. This method offers a reliable, cost-effective, and non-invasive solution to assist medical professionals in diagnosing brain tumors.
Full Text Attachment
