Robust fitting of a point distribution model of the prostate using genetic algorithms

被引：0
|
作者：
Cosío, FA [1 ]
机构：
[1] Univ Nacl Autonoma Mexico, CCADET, Mexico City 04510, DF, Mexico
来源：
IMAGE ANALYSIS AND RECOGNITION, PT 2, PROCEEDINGS | 2004年 / 3212卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A Point Distribution Model (PDM) of the prostate has been constructed and used to automatically outline the contour of the gland in transurethral ultrasound images. We developed a new, two stage, method: first the PDM is fitted, using a multi-population genetic algorithm, to a binary image produced from Bayesian pixel classification. This contour is then used during the second stage to seed the initial population of a simple genetic algorithm, which adjusts the PDM to the prostate boundary on a grey level image. The method is able to find good approximations of the prostate boundary in a robust manner. The method and its results on 4 prostate images are reported.
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页码：76 / 83
页数：8
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