Atmosukarto Indriyati, Shapiro Linda G, Heike Carrie
Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA, 98105.
Seattle Children's Hospital, Craniofacial Center.
Proc IAPR Int Conf Pattern Recogn. 2010;2010:2444-2447. doi: 10.1109/ICPR.2010.598.
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].
颅面疾病通常会导致各种头部形状畸形。这项工作的目标是量化患有一种名为22q11.2缺失综合征的颅面疾病患者不同面部异常中表现出的各种三维形状变化。遗传编程(GP)被用于学习不同的三维形状量化。实验结果表明,与人类专家和现有计算机算法相比,遗传编程方法实现了更高的分类率[1],[2]。