Medical object extraction model based on regional energyminimization and active contour model
基于区域能量最小和主动轮廓模型的医学目标提取

In order to solve the problems of traditional active contour models, which move in a high speed on strong edge or leak out on weak edge, this paper proposed a medical object extraction model which was based on regional energy minimization and active contour model. The model employed objects' statistical intensity distribution in a level set framework, and expressed energy function as an integral of probability of pixels belonging to objects. The energy function was minimized in a level set framework which led to a iterating equation. At the same time, an edge based speed constrain term was able to slow down the active contours when they steped over a steep boundary of the objects, which made the extraction procedure more convergent and accurately. As shown in the experiments of coronary and mitral valve extraction with comparison with several classical models and manual outline, the proposed model is able to extraction medical objects in an automatic way and the results are also more robust, accurate, and convergent than several traditional models.