使用遗传规划学习三维颅面形状量化。

Indriyati Atmosukarto, Linda G Shapiro, Carrie Heike
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引用次数: 10

摘要

颅面疾病通常导致各种头部形状畸形。这项工作的目标是量化患有22q11.2缺失综合征颅面疾病的个体在不同面部异常中表现出的各种3D形状变化。采用遗传规划(GP)来学习不同的三维形状量化。实验结果表明,GP方法比人类专家和现有计算机算法的分类率更高[1],[2]。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The Use of Genetic Programming for Learning 3D Craniofacial Shape Quantifications.

The Use of Genetic Programming for Learning 3D Craniofacial Shape Quantifications.

The Use of Genetic Programming for Learning 3D Craniofacial Shape Quantifications.

The Use of Genetic Programming for Learning 3D Craniofacial Shape Quantifications.

Craniofacial disorders commonly result in various head shape dysmorphologies. The goal of this work is to quantify the various 3D shape variations that manifest in the different facial abnormalities in individuals with a craniofacial disorder called 22q11.2 Deletion Syndrome. Genetic programming (GP) is used to learn the different 3D shape quantifications. Experimental results show that the GP method achieves a higher classification rate than those of human experts and existing computer algorithms [1], [2].

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