代表文章 [1] Shuyi LI; Min Dong; Guangming Du; Xingrun Xing ; Attention Dense-U-Net for Automatic Breast Mass Segmentation in Digital Mammogram, IEEE Access, 2019, 7: 59037-59047 [2] Dong Min; Lu Xiangyu; Ma,Yide; Guo Yanan; Ma Yurun; Wang Keju ; An Efficient Approach for Automated Mass Segmentation and Classification in Mammograms, Journal of Digital Imaging, 2015,28(5): 613-625 [3] Guangming Du; Min Dong; Yi Sun; Shuyi LI; Xiaomin Mu; Hongbin Wei; Lei Ma; Bang Liu ; A new method for detecting architectural distortion in mammograms by nonSubsampled contourlet transform and improved PCNN, Applied Sciences-Basel, 2019, 9(22): 1-19 [4] Min Dong; Jiuwen Zhang; Yide Ma ; Image denoising via bivariate shrinkage function based on a new structure of dual contourlet transform, Signal Processing, 2015, 109: 25-37 [5] Min Dong; Dezhen Li; Kaixiang Li; Junpeng Xu ; TSDNet: a new multiscale texture surface defect detection model, Applied Sciences-Basel, 2023, 13(3289): 1-18 [6]Yang Zhen; Dong Min; Guo Yanan; Gao Xiaoli; Wang Keju; Shi Bin; Ma Yide(*), A new method of micro-calcifications detection in digitized mammograms based on improved simplified PCNN. Neurocomputing, 2016.12, 218: 79-90 [7] Guo Yanan; Dong Min; Yang Zhen; Gao Xiaoli; Wang Keju; Luo Chongfan; Ma Yide; Zhang Jiuwen: A new method of detecting micro-calcification clusters in mammograms using contourlet transform and non- linking simplified PCNN. Computer Methods and Programs in Biomedicine, 2016.7, 130: 31-45 |
