A Method for Eztraction of Interesting Region in Mammograph Based on Two-Dimensional Principal Component Analysis

摘要：

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 (2DPCA) to extract the interesting region (IR) 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.

作者: LU Wen ZHANG Guang-Yu

作者单位: Taishan Medical College, Taian, Shandong, China

会议类型: 国际会议

会议名称: Yangtze River 2009 International Conference on Medical Imaging Physics & The 5th National Annual Meeting of Medical Imaging Physics(长江2009国际医学影像物理和工程大会暨第五届中国医学影像物理学术年会ICMIP2009)

会议地点: 南京

会议语种:英文

页码: 202-204

在线出版日期: 2009-10-23（万方平台首次上网日期，不代表论文的发表时间）