Classifying small lesions on breast MRI through dynamic enhancement pattern characterization
MLMI(2011)
摘要
Dynamic characterization of the lesion enhancement pattern can improve the classification performance of small diagnostically challenging lesions on dynamic-contrast enhanced MRI. This involves extraction of texture features from all post-contrast images of the lesion rather than using the first post-contrast image alone. In this study, statistical texture features derived from gray-level co-occurrence matrices are extracted from all five post-contrast images of 60 lesions and then used in a supervised learning task with a support vector regressor. Our results show that this approach significantly improves the performance of classifying small lesions (p
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关键词
small lesion,lesion enhancement pattern,breast mri,statistical texture,post-contrast image,dynamic-contrast enhanced mri,dynamic characterization,small diagnostically,dynamic enhancement pattern characterization,gray-level co-occurrence matrix,texture feature,classification performance
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