A Statistical Shape lVLodel Using 2D-Principal Component Analysis from Few Medical Samples and Its Evaluation

摘要：

Since the medical training samples are very lim-ited, it is difficult to construct a statistical shape model with good generalization using few samples. In this paper, we propose a novel statistical shape modeling method using 2D PCA. The 3D shape is represented as a matrix by spherical parameterization. The experiments showed that our proposed method can reconstruct statistical shape model with good generalization even using fewer samples.

关键词： Statistical shape model Spherical parameteriza-tion 3-D shape representation 2-Dimensional Principal Com-ponent Analysis few Medical Sample

作者: Tomoko Tateyama Taishi Tanaka Shinya Kohara Amir Hossein Foruzan Akira Furukawa Yen-Wei Chen

作者单位: lntelligent Image Processing Lab, College of In.formation Science and Engineering,Ritsumeikan Unive lntelligent Image Processing Lab, College of In.formation Science and Engineering,Ritsumeikan Unive Departrrient of Radiology Shiga University of Medical Science, Shiga, Japan

会议类型: 国际会议

会议名称: The 2nd International Conference on Software Engineering and Data Mining(IEEE 第二届国际软件工程和数据挖掘学术大会 SEDM 2010)

会议地点: 成都

会议语种:英文

页码: 631-634

在线出版日期: 2010-06-23（万方平台首次上网日期，不代表论文的发表时间）