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2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
How to model shape variations plays an important role in active shape models that is widely used in modelbased medical image segmentation, and principal component analysis is a common approach for this task. Recently, different tensor-based dimension reduction methods have been proposed and have achieved better performances than PCA in face recognition. However, how they perform in modeling 3D shape variations of organs in terms of reconstruction errors in medical image analysis is stilldoi:10.1109/iembs.2009.5334398 pmid:19964869 fatcat:2d647k3lfjhbtfevki3lrlcnz4