1 Objective In mammography computer-aided diagnosis the automatic extraction of interesting region is one of the most difficult problems. This paper presents a method based on two-dimensional principal component analysis to extract the interesting region automatically. First, preprocess the mammograms, and then, extract mammography features by 2DPCA method and edge-detection algorithm. Finally, extract IR by neural network classifier. 60 cases were analyzed and 100 images which from Shandong m...更多
1 Objective In mammography computer-aided diagnosis the automatic extraction of interesting region is one of the most difficult problems. This paper presents a method based on two-dimensional principal component analysis to extract the interesting region automatically. First, preprocess the mammograms, and then, extract mammography features by 2DPCA method and edge-detection algorithm. Finally, extract IR by neural network classifier. 60 cases were analyzed and 100 images which from Shandong medical imaging research institute were used in this investigation. The results show that a better positive detection ratio is obtained with this method. This approach can obtain better extraction accuracy by integrating 2DPCA, edge-detection algorithm and neural networks.收起
