A statistical shape model using 2D-principal component analysis from few medical samples and its evaluation

Tomoko Tateyama, Taishi Tanaka, Shinya Kohara, Amir Hossein Foruzan, Akira Furukawa, Yen Wei Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Since the medical training samples are very limited, 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.

Original languageEnglish
Title of host publication2nd International Conference on Software Engineering and Data Mining, SEDM 2010
Pages663-666
Number of pages4
Publication statusPublished - 2010
Externally publishedYes
Event2nd International Conference on Software Engineering and Data Mining, SEDM 2010 - Chengdu, China
Duration: 23-06-201025-06-2010

Publication series

Name2nd International Conference on Software Engineering and Data Mining, SEDM 2010

Conference

Conference2nd International Conference on Software Engineering and Data Mining, SEDM 2010
Country/TerritoryChina
CityChengdu
Period23-06-1025-06-10

All Science Journal Classification (ASJC) codes

  • Software

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