Durikovic R, Kaneda K, Yamashita H
Electric Machinery Laboratory, Faculty of Engineering, Hiroshima University, Japan.
Med Biol Eng Comput. 1998 May;36(3):276-84. doi: 10.1007/BF02522471.
A system is considered for segmenting noisy intensity images and consequent three-dimensional object reconstruction from a set of planar contours. A new semi-automatic method for the extraction of contours from a sequence of cross-sectional images based on an active contour model (ACM) is proposed. The dynamic ACM proceeds along the sequence of cross-sections following a non-rigid motion, in accordance with the organ boundary. Image texture information is also employed in the model. Problems associated with topological reconstruction from planar contours are addressed, and several criteria promoting semi-automatic topological reconstruction are introduced. The proposed system is successfully applied to the processing of real data related to animal embryonic organs, proving that the system allows detailed modelling of irregular objects. The reconstructed models can be observed in wire-frame, solid, transparent or stereoscopic semi-transparent format. The human-computer interaction implemented in the procedure assists with problems of feature identification and object manipulation about an arbitrary axis.
本文考虑了一种用于分割噪声强度图像并从一组平面轮廓进行三维物体重建的系统。提出了一种基于主动轮廓模型（ACM）从一系列横截面图像中提取轮廓的新半自动方法。动态ACM根据器官边界，沿着横截面序列进行非刚性运动。该模型还利用了图像纹理信息。解决了与从平面轮廓进行拓扑重建相关的问题，并引入了一些促进半自动拓扑重建的标准。所提出的系统成功应用于与动物胚胎器官相关的真实数据处理，证明该系统允许对不规则物体进行详细建模。重建模型可以以线框、实体、透明或立体半透明格式进行观察。该过程中实现的人机交互有助于解决特征识别和围绕任意轴的物体操纵问题。
