Although various segmentation or cutout schemes have been well-developed for both 2D and 3D images, it remains a challenging problem to cutout an object from a volume dataset in an intuitive and convenient fashion. Most of existing volume cutout algorithms operate on 2D slice images, and extend the extracted information to the 3D counter. In this paper, we propose a novel volume object cutout algorithm which allows users to select 3D points by drawing strokes onto the volume rendering images. A set of 3D points is collected by casting through the drawn strokes, followed by a refinement process based on the k-mean clustering method to obtain high confidential result. Taking these refined points as seed points, the graph cut algorithm is employed to accurately and quickly extract the intended object. Experimental results demonstrate the effectiveness of our algorithm.%针对三维体对象抠取的相关工作中存在的尚多不足,提出一种体对象抠取算法.首先计算出与用户勾画结果相关的三维数据点,然后基于K-means聚类方法标记出高置信度的属于目标对象和无关对象的三维数据点,并以此作为种子点,借助基于能量优化的图割算法最终得到正确的体对象抠取结果.用户只需直接在体绘制的二维颜色叠加结果上通过简单的勾画指定目标对象和无关对象,即可抠取出感兴趣的体结构.最后通过实验说明了该算法的有效性.
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