A New Region-Based Active Contours Combined with the GAC Model
Bo Wu, Shuyan Xu, Yanpeng Feng, Shuang Zhang · 2018
Intensity inhomogeneities often cause considerable difficulties in the quantitative analysis of images, especially for magnetic resonance (MR) images. It is hard to segment such images by using traditional level set based upon segmentation models. In order to come over these difficulties, in view of the experience of the predecessors, we proposed a new region-based active contour model. This model uses adaptive region force and the object's boundary information to segment images we greatly interested in. The region-based force has local information which can handle intensity inhomogeneity, the time-consumption is also optimistic. The GAC model plays a role which can help to get through the weak boundary. Experimental results for synthetic and real images demonstrate the superior performance of our model.