Provably Efficient and Fast Technique for Determining the Size of a Brain Tumor in T1 MRI Images

This work proposes an efficient a nd effective technique for determining the size of neoplasms in the brain using image processing. The cerebral hemispheres make up the largest part of the human brain, and abnormal growth of cells within them can lead to the development of neoplasms, or brain tumors. Many tumors are believed to occur for unknown reasons, which highlights the importance of annual check-ups to detect any early signs of a tumor. Image processing is a crucial component of these annual check-ups, as it can identify any changes that may have occurred in the brain since the previous check-up. This work proposes a new method that can segment the tumor through the skull and estimate its size using MRI images. The proposed method involves three steps: first, extracting t he b rain from the skull; second, applying thresholding to identify abnormal cells and segment the neoplasm; and finally, estimating t he size of the neoplasm in a fast manner. To validate the results, a comparison with other techniques such as K-means and C-means is performed. Overall, this proposed method provides a promising approach to detecting and measuring neoplasms in the brain, which could ultimately improve the diagnosis and treatment of these potentially life-threatening conditions.