Li Shunan, Wan Baikun, Ma Zhenhe, Wang Ruiping
Department of Biomedical Engineering, Tianjin University, Tianjin 300072, China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2005 Apr;22(2):360-2.
In order to preprocess mammograms for diagnosing the early cases of breast cancer and improving the computational efficiency in the computer-aided detection of micro-calcifications in mammograms, we have advanced a novel processing technique for the extraction of micro-calcification region of interest (MROI). The proposed method is based on a three-step procedure: (1) the mammogram is divided into sub-images of the same size; (2) the wavelet multi-resolution method is conducted on the sub-images, and the parameters related to wavelet transform and threshold T are discussed according to rho; (3) the classification of sub-images is determined by T. It is tested with 20 mammograms and the results show that the method can achieve a true positive rate as high as 89.7% with a false positive rate as low as 2.1%.
为了对乳房X光照片进行预处理以诊断早期乳腺癌病例,并提高乳房X光照片中微钙化的计算机辅助检测的计算效率,我们提出了一种用于提取感兴趣的微钙化区域(MROI)的新型处理技术。所提出的方法基于三步程序:(1)将乳房X光照片划分为相同大小的子图像;(2)对子图像进行小波多分辨率方法,并根据rho讨论与小波变换和阈值T相关的参数;(3)由T确定子图像的分类。用20张乳房X光照片进行了测试,结果表明该方法可以实现高达89.7%的真阳性率和低至2.1%的假阳性率。