IEEE Trans Vis Comput Graph. 2013 Feb;19(2):331-43. doi: 10.1109/TVCG.2012.134. Epub 2012 Jun 12.
We describe a snake-type method for shape registration in 2D and 3D, by fitting a given polygonal template to an acquired image or volume data. The snake aspires to fit itself to the data in a shape which is locally As-Similar-As-Possible (ASAP) to the template. Our ASAP regulating force is based on the Moving Least Squares (MLS) similarity deformation. Combining this force with the traditional internal and external forces associated with a snake leads to a powerful and robust registration algorithm, capable of extracting precise shape information from image data.
我们描述了一种用于 2D 和 3D 形状配准的蛇形方法,通过将给定的多边形模板拟合到获取的图像或体积数据上。蛇希望将自身拟合到数据上,使其形状在局部上尽可能与模板相似(ASAP)。我们的 ASAP 调节力基于移动最小二乘(MLS)相似变形。将这种力与传统的与蛇相关的内部和外部力相结合,导致一种强大而稳健的配准算法,能够从图像数据中提取精确的形状信息。