Brain Tumor Detection from MRI
A novel method is presented by first converting MRI images to grayscale for standard evaluation and then applies advanced filters to reduce noise and interference, enhancing image clarity and accuracy of MRI-based brain tumor detection.
Abstract
Early diagnosis of brain tumors is challenging due to noise and environmental interference distorting MRI images. This paper presents a novel method that addresses this issue by first converting MRI images to grayscale for standard evaluation. It then applies advanced filters to reduce noise and interference, enhancing image clarity. Subsequent image segmentation techniques delineate tumor edges, which is crucial for early detection, especially when edges are unclear. This innovative approach significantly improves the accuracy and effectiveness of the MRI-based brain tumor detection, potentially revolutionizing early detection and enhancing patient outcomes.