基于生理特征的乳腺X线图像多视图分析坐标系

曹霖; 陈后金; 李居朋; 程琳

doi:10.11999/JEIT160193

基于生理特征的乳腺X线图像多视图分析坐标系

doi: 10.11999/JEIT160193

曹霖¹,
陈后金^1, ,,
李居朋¹,
程琳²

1.
(北京交通大学电子信息工程学院北京 100044) ②(北京大学人民医院乳腺中心北京 100044)

基金项目:

国家自然科学基金(61271305)，北京市科技计划课题(D151100000415002)，中央高校基本科研业务费(2015JBM015)

计量
- 文章访问数: 1400
- HTML全文浏览量: 177
- PDF下载量: 519
- 被引次数: 0
出版历程
- 收稿日期: 2016-03-01
- 修回日期: 2016-07-08
- 刊出日期: 2017-01-19

Physiological Features Based Coordinate System for Multi-view Analysis in Mammograms

1.
(School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China)
2.
(Breast Center of Peking University People,s Hospital, Beijing 100044, China)

Funds:

The National Natural Science Foundation of China (61271305), Beijing Municipal Science and Technology Project (D151100000415002), The Fundamental Research Funds for the Central Universities (2015JBM015)

摘要

摘要: 该文针对乳腺X线图像病变的多视图检测与分析问题，建立了一种基于乳房生理特征的多视图坐标系。通过轴位、中侧斜位视图图像中的乳头、胸肌典型生理特征的提取，以及乳房边缘的椭圆拟合，建立乳腺X线图像多视图分析坐标系，可将乳腺X线图像双侧四视图经非线性映射至同一坐标框架内。以北京大学人民医院乳腺中心提供的图像库为实验数据，从生理特征定位精度、兴趣区域匹配精度等多方面进行坐标系匹配准确度的测试与验证，结果表明该坐标系有助于乳腺X线图像，特别是致密型图像的多视图病变检测。
- 乳腺X线图像 /
- 多视图分析 /
- 坐标系 /
- 生理特征 /
- 区域匹配
Abstract: A breast coordinate system based on physiological features is developed for multi-view analysis in mammograms. It is constructed according to the locations of nipple, pectoral muscle and the fitted breast boundary. The breast regions in mammograms are mapped into a parameter frame because of the coordinate system. Experiments are implemented on data set of Breast Cancer of Peking University Peoples Hospital. The performance of locating the physiological features and matching the regions of interest is evaluated. Results show that the proposed coordinate system could achieve favorable performance and facilitate the multi-view analysis in mammograms.
- Mammogram /
- Multi-view analysis /
- Coordinate system /
- Physiological features /
- Region matching

HTML全文

参考文献(17)

ANDERSON B O, YIP C H, SMITH R A, et al. Guideline implementation for breast healthcare in low-income and middle-income countries[J]. Cancer, 2008, 113(S8): 2221-2243. doi: 10.1002/cncr.23844.

MASKARINEC G, MENG L, and URSIN G. Ethnic differences in mammographic densities[J]. International Journal of Epidemiology, 2001, 30(5): 959-965. doi: 10.1093 /ije/30.5.959.

MENCATTINI A, SALMERI M, and CASTI P. Bilateral asymmetry identification for the early detection of breast cancer[C]. 2011 IEEE International Workshop on Medical Measurements and Applications Proceedings (MeMeA), Bari, Italy, 2011: 613-618. doi: 10.1109/MeMeA.2011.5966746.

CASTI P, MENCATTINI A, SALMERI M, et al. Masking procedures and measures of angular similarity for detection of bilateral asymmetry in mammograms[C]. The 4th IEEE International Conference on E-Health and Bioengineering, Iasi, Romania, 2013: 1-4. doi: 10.1109/EHB.2013.6707258.

CASTI P, MENCATTINI A, SALMERI M, et al. Analysis of structural similarity in mammograms for detection of bilateral asymmetry[J]. IEEE Transactions on Medical Imaging, 2015, 24(2): 662-671. doi: 10.1109/TMI.2014. 2365436.

MAGNA G, JAYARAMAN S V, CASTI P, et al. Adaptive classification model based on artificial immune system for breast cancer detection[C]. 2015 XVIII AISEM Annual Conference, Trento, Italy, 2015: 1-4. doi: 10.1109/AISEM. 2015.7066842.

LI Yanfeng, CHEN Houjin, YANG Yongyi, et al. A bilateral analysis scheme for false positive reduction in mammogram mass detection[J]. Computers in Biology and Medicine, 2015, (57): 84-95. doi: 10.1016/j.compbiomed.2014.12.007.

KELDER A, ZIGEL Y, LEDERMAN D, et al. A new computer-aided detection scheme based on assessment of local bilateral mammographic feature asymmetry-a preliminary evaluation[C]. 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Milan, Italy, 2015: 6394-6397. doi: 10.1109/EMBC. 2015.7319856.

王之琼, 王培, 于戈, 等. 双侧特征融合的乳腺肿块检测[J]. 计算机辅助设计与图形学学报, 2015, 27(6): 1024-1031.

WANG Zhiqiong, WANG Pei, YU Ge, et al. Breast tumor detection on fusion of bilateral feature[J]. Journal of Computer-Aided Design Computer Graphics, 2015, 27(6): 1024-1031.

CAO Lin, CHEN Houjin, LI Jupeng, et al. A coordinate system for multi-view analysis of mammograms[C]. The 6th International Conference on Mechanical and Electronics Engineering, Beijing, China, 2014: 481-487. doi: 10.2495/ ICMIIE140701.

BRANDT S S, KAREMORE G, and KARSSEMEIJER N. An anatomically oriented breast coordinate system for mammogram analysis[J]. IEEE Transactions on Medical Imaging, 2011, 30(10): 1841-1851. doi: 10.1109/TMI.2011. 2155082.

GEORGSSON F. Anatomical coordinate system for bilateral registration of mammograms[C]. 13th Scandinavian Conference on Image Analysis, Halmstad, Sweden, 2003: 335-342. doi: 10.1007/3-540-45103-X_46.

KITA Y, HIGHNAM R, and BRADY M. Correspondence between different view breast X rays using curved epipolar lines[J]. Computer Vision and Image Understanding, 2001, 83(1): 38-56. doi: 10.1006/cviu.2001.0908.

PU Jiantao, ZHENG Bin, LEADER J K, et al. An ellipse- fitting based method for efficient registration of breast masses on two mammographic views[J]. Medical Physics, 2008, 35(2): 487-494. doi: 10.1118/1.2828188.

MARTIN K E, HELVIE M A, ZHOU C, et al. Mammographic density measured with quantitative computer-aided method comparison with radiologists estimates and BI-RADS categories[J]. Radiology, 2006, 240(3): 656-665. doi: 10.1148/radiol.2402041947.

WIRTH M A, CHOI C, and JENNINGS A. A nonrigid-body approach to matching mammograms[C]. Seventh International Conference on Image Processing and Its Applications, Manchester, UK, 1999: 484-488. doi: 10.1049/ cp:19990369.

施引文献

资源附件(0)

访问统计