Detection of Architectural Distortion in Mammograms
-
摘要: 针对乳腺X线图像结构扭曲 (Architectural distortion,AD)检测假阳性率偏高的问题,提出了一种新的乳腺X线图像结构扭曲 检测方法相似度收敛指数(Similarity convergence index,SCI)方法.首先利用马氏距离比计算出毛刺的相似度,然后通过计算相似度加权的收敛指数增强放射状毛 刺,最后提取出收敛指数的局部最大值作为候选点,并对这些候选点进行分类,检测出结构扭曲. 该方法在Mini-MIAS (Mammographic Image Analysis Society)乳腺图像和北京大学人民医院乳腺中心乳腺图像上进行验证,实验结果表明,本文提出的方法有效降低了假阳 性率,同时适用于脂肪型乳腺X线图像和致密型乳腺X线图像.Abstract: For the problem of the high false positive rate in the detection of architectural distortion (AD) in mammograms, a novel method called similarity convergence index (SCI) is proposed. Firstly the spiculation similarity based on Mahalanobis distance is presented and used to compute the SCI to enhance radiating spiculations. Then local maximum values of SCI are extracted as AD candidates, and lastly these candidates are classified into AD and normal tissues. The proposed method is evaluated on mammograms from the Mini-MIAS (Mammographic Image Analysis Society) and mammograms from the Breast Disease Center of Peking University People's Hospital. The results show that the proposed detection method can reduce the false positive rate significantly, and can be applied to both fat and compact mammograms.
-
[1] 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 [2] [4] 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] [6] 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 [4] [7] 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 [5] [8] 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 [6] [9] 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 [7] 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 [8] 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 [9] 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) [10] Xing Xiao-Jie, Xu Xiang-Min, Xiao Yue, Zhou Feng-Le. Detection algorithm on mass focus in mammary dense region. Microcomputer Information, 2009, 25(18): 174-176 (邢晓洁, 徐向民, 肖跃, 周丰乐. 乳腺X线图像中致密区域肿块的检测算法. 微计算机信息, 2009, 25(18): 174-176) [11] 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
点击查看大图
计量
- 文章访问数: 1953
- HTML全文浏览量: 79
- PDF下载量: 678
- 被引次数: 0