TY - GEN
T1 - A statistical shape model using 2D-principal component analysis from few medical samples and its evaluation
AU - Tateyama, Tomoko
AU - Tanaka, Taishi
AU - Kohara, Shinya
AU - Foruzan, Amir Hossein
AU - Furukawa, Akira
AU - Chen, Yen Wei
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=77956519706&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77956519706&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:77956519706
SN - 9788988678213
T3 - 2nd International Conference on Software Engineering and Data Mining, SEDM 2010
SP - 663
EP - 666
BT - 2nd International Conference on Software Engineering and Data Mining, SEDM 2010
T2 - 2nd International Conference on Software Engineering and Data Mining, SEDM 2010
Y2 - 23 June 2010 through 25 June 2010
ER -