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

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.