MATLAB Implementation of Medical Image Segmentation for Brain Tumor Detection Using Level Set Methods

This article presents a MATLAB-based implementation for medical image segmentation, specifically focusing on brain tumor detection using level set methods. The program utilizes active contour modeling through partial differential equations to accurately segment tumor boundaries from medical images. Key implementation aspects include initialization of level set functions, evolution equations for boundary propagation, and regularization terms for smooth contour development. The algorithm handles intensity inhomogeneity common in medical scans through region-based energy minimization approaches. Additionally, the package contains comprehensive testing modules that validate segmentation accuracy using metrics like Dice coefficient and Hausdorff distance. These test routines include sample medical images, ground truth data comparisons, and performance evaluation scripts to help researchers understand and apply these techniques effectively in clinical image analysis scenarios.