Improved GVF external force based on modified normal flow
Yuhua Yao, Lixiong Liu, Lejian Liao, Ming Wei, Xueming Yin, Xianglin Yang, Yinghui Li · 2012
Active contours are one of the most successful image segmentation methods in image processing and computer vision field. Their main limitations are high noise sensitivity and poor capture range from the target object. One of the most promising approaches for solving these limitations is the gradient vector flow (GVF). However, GVF still has improving space in converging to concavities and noise robustness. Here we propose a novel GVF external force based on modified normal flow for improving contour performance. This novel external force field is insensitive to noises and may converge to concavities. We compared the proposed method with other methods by synthetic images and real medical images. Experimental results illustrated that the proposed method had achieved more accurate segmentation for noise robustness and concavity convergence.