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- W2348280089 abstract "An improved ASM method for segmentation of left ventricle tagged MR images is presented.Based on the idea of fea ture fusion,the Canonical Correlation Analysis(CCA) is used to combine the features extracted form tagged MR images by LM filter bank.Then,a classifier is constructed to determine edge point using SVM.CCA can decrease the classification error and improve the classification performance.Instead of sampling the normalized derivative profiles,the feature at each position along the profile perpendicular to the object contour is fed into a trained classifier to determine the edge point.The method is validated on different frame and slice of tagged MR images.Experimental results show that the method can achieve a high accurate and robust performance." @default.
- W2348280089 created "2016-06-24" @default.
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- W2348280089 date "2010-01-01" @default.
- W2348280089 modified "2023-09-28" @default.
- W2348280089 title "Segmentation of left ventricle from Tagged MR images based on ASM and feature fusion strategy" @default.
- W2348280089 hasPublicationYear "2010" @default.
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