Multidimensional alignment using the Euclidean distance transform

被引：57

作者：

Kozinska, D ^{[1
]}

Tretiak, OJ

Nissanov, J

Ozturk, C

机构：

[1] M Nencki Inst Expt Biol, PL-02093 Warsaw, Poland

[2] Drexel Univ, Philadelphia, PA 19104 USA

来源：

GRAPHICAL MODELS AND IMAGE PROCESSING | 1997年 / 59卷 / 06期

基金：

美国国家卫生研究院;

关键词：

D O I：

10.1006/gmip.1997.0447

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

We present a methodology for alignment of multidimensional data sets that is based on the Euclidean distance transform and the Marquardt-Levenberg optimization algorithm. The proposed approach operates on pixel or voxel descriptions of objects to be matched and estimates the parameters of a space transformation for optimal alignment of objects. The computational cost of an algorithm developed with this method is estimated. The methodology is tested by developing an algorithm for rigid body transformation alignment of three-dimensional data sets. Tests with synthetic and real objects indicate that the method is accurate, reliable, and robust. (C) 1997 Academic Press.

引用

页码：373 / 387

页数：15