Medical Image Segmentation Using GVF Algorithm in MATLAB

This project implements medical image segmentation using the Gradient Vector Flow (GVF) algorithm based on MATLAB, primarily designed for 2D medical image segmentation. The GVF algorithm is a sophisticated medical image segmentation method that utilizes gradient vector flow fields to capture boundary features. Through MATLAB implementation, the algorithm effectively segments medical images by creating a diffusion process that extends gradient vectors from image edges into homogeneous regions. Medical image segmentation represents a crucial computational task that enables physicians to accurately identify and analyze specific anatomical structures and regions within medical imagery. The MATLAB implementation typically involves key functions such as: calculating image gradients using edge detection operators, solving partial differential equations for vector field diffusion, and iterative convergence to optimal boundary locations. The algorithm's application significantly enhances the efficiency and accuracy of medical image analysis, holding substantial importance for both medical research and clinical practice. Key implementation steps include preprocessing medical images, initializing active contour models, computing GVF fields using numerical methods like finite differences, and evolving contours toward object boundaries through energy minimization techniques.