Genetic algorithm-based interactive segmentation of 3D medical images

被引:68
作者
Cagnoni, S
Dobrzeniecki, AB
Poli, R
Yanch, JC
机构
[1] Univ Parma, Dept Comp Engn, I-43100 Parma, Italy
[2] Harvard Univ, Sch Med, Cambridge, MA 02138 USA
[3] Univ Birmingham, Sch Comp Sci, Birmingham B15 2TT, W Midlands, England
[4] MIT, Whitaker Coll Hlth Sci & Technol, Cambridge, MA 02139 USA
关键词
genetic algorithm; elastic contour; filter;
D O I
10.1016/S0262-8856(98)00166-8
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This article describes a method for evolving adaptive procedures for the contour-based segmentation of anatomical structures in 3D medical data sets. With this method, the user first manually traces one or more 2D contours of an anatomical structure of interest on parallel planes arbitrarily cutting the data set. Such contours are then used as training tramples for a genetic algorithm to evolve a contour detector. By applying the detector to the rest of the image sequence it is possible to obtain a full segmentation of the structure. The same detector can then be used to segment other image sequences of the same sort. Segmentation is driven by a contour-tracking strategy that relies on an elastic-contour model whose parameters are also optimized by the genetic algorithm. We report results obtained on a software-generated phantom and on real tomographic images of different sorts. (C) 1999 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:881 / 895
页数:15
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