WHO Media Centre. WHO cancer fact sheets [Online], available: http://www.who.int/mediacentre/factsheets/fs297/ en, January 26, 2013
[2]
Baker J A, Rosen E L, Lo J Y, Gimenez E I, Walsh R, Soo M S. Computer-aided detection (CAD) in screening mammography: Sensitivity of commercial CAD systems for detecting architectural distortion. American Journal of Roentgenology, 2003, 181(4): 1083-1088
[3]
Sampat M P, Whitman G J, Markey M K, Bovik A C. Evidence based detection of spiculated masses and architectural distortions. In: Proceedings of the 2005 SPIE 5747: Medical Imaging. San Diego, USA: SPIE, 2005. 26-37
[4]
Ayres F J, Rangayyan R M. Reduction of false positives in the detection of architectural distortion in mammograms by using a geometrically constrained phase portrait model. International Journal of Computer Assisted Radiology and Surgery, 2007, 1(6): 361-369
[5]
Gong Zhu-Lin, Chen Ying, Zhang Lu. The detection of architectural distortion in mammograms by using support vector machine. Journal of Shanghai Jiaotong University, 2009, 43(7): 1038-1042 (龚著琳, 陈瑛, 章鲁. 用支持向量机检测乳腺X线影像中的结构扭曲. 上海交通大学学报, 2009, 43(7): 1038-1042)
[6]
Tang J S, Rangayyan R M, Xu J, El Naqa I, Yang Y Y. Computer-aided detection and diagnosis of breast cancer with mammography: recent advances. IEEE Transactions on Information Technology in Biomedicine, 2009, 13(2): 236-251
[7]
National Cancer Institute. NCI cancer fact sheets [Online], available: http://www.cancer.gov/cancertopics/types/ breast, June 3, 2013
[8]
American College of Radiology. About BI-RADS [Online], available: http://www.birads.at/info.html, January 12, 2011
[9]
Rangayyan R M, Ayres F J. Gabor filters and phase portraits for the detection of architectural distortion in mammograms. Medical and Biological Engineering and Computing, 2006, 44(10): 883-894
[10]
Guo Q, Shao J, Ruiz V. Investigation of support vector machine for the detection of architectural distortion in mammographic images. Journal of Physics: Conference Series, 2005, 15: 88-94
[11]
Banik S, Rangayyan R M, Desautels J E L. Detection of architectural distortion in prior mammograms. IEEE Transactions on Medical Imaging, 2011, 30(2): 279-294
[12]
Biswas S K, Mukherjee D P. Recognizing architectural distortion in mammogram: a multiscale texture modeling approach with GMM. IEEE Transactions on Biomedical Engineering, 2011, 58(7): 2023-2030
te Brake G M, Karssemeijer N, Hendriks J H. An automatic method to discriminate malignant masses from normal tissue in digital mammograms. Physics in Medicine and Biology, 2000, 45(10): 2843-2857
[15]
Suckling J. The mammographic image analysis society digital mammogram database [Online], available: http://peipa. essex.ac.uk/info/mias.html, December 11, 2013