首页> 外文会议>Scandinavian Conference on Image Analysis(SCIA 2007); 20070610-14; Aalborg(DK) >Sparse Statistical Deformation Model for the Analysis of Craniofacial Malformations in the Crouzon Mouse
【24h】

Sparse Statistical Deformation Model for the Analysis of Craniofacial Malformations in the Crouzon Mouse

机译:Crouzon小鼠颅面畸形的稀疏统计变形模型

获取原文
获取原文并翻译 | 示例

摘要

Crouzon syndrome is characterised by the premature fusion of cranial sutures. Recently the first genetic Crouzon mouse model was generated. In this study, Micro CT skull scannings of wild-type mice and Crouzon mice were investigated. Using nonrigid registration, a wild-type craniofacial mouse atlas was built. The atlas was registered to all mice providing parameters controlling the deformations for each subject. Our previous PCA-based statistical deformation model on these parameters revealed only one discriminating mode of variation. Aiming at distributing the discriminating variation over more modes we built a different model using Independent Component Analysis (ICA). Here, we focus on a third method, sparse PCA (SPCA), which aims at approximating the properties of a standard PCA while introducing sparse modes of variation. The results show that SPCA outperforms both ICA and PCA with respect to the Fisher discriminant, although many similarities are found with respect to ICA.
机译:Crouzon综合征的特征是颅骨缝线过早融合。最近,产生了第一个遗传性Crouzon小鼠模型。在这项研究中,对野生型小鼠和Crouzon小鼠的Micro CT颅骨扫描进行了研究。使用非刚性配准,构建了野生型颅面小鼠图集。该图集已注册给所有小鼠,并提供了控制每个对象变形的参数。我们先前基于PCA的这些参数的统计变形模型揭示了仅一种区分模式。为了在更多模式下分配差异,我们使用独立分量分析(ICA)建立了一个不同的模型。在这里,我们重点介绍第三种方法:稀疏PCA(SPCA),其目的是在引入稀疏变化模式的同时逼近标准PCA的属性。结果表明,尽管发现与ICA有许多相似之处,但SPCA在Fisher判别方面优于ICA和PCA。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号