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乳腺摄片的计算机辅助诊断技术在乳腺癌诊断中的新进展 被引量:1

Advances in Computer-aided Diagnosis for Breast Cancer in Mammography
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摘要 在全球范围内,乳腺癌是严重影响妇女身心健康的常见病之一。早期发现、早期诊断、早期治疗,是降低乳腺癌死亡率的关键。第二次阅片会明显提高乳腺癌诊断的灵敏度。然而纵观国内外文献,因乳腺图像数据库的来源和计算机辅助诊断系统方法的应用存在很大分歧,所以不同试验结果很难具有可比性。因此,计算机辅助诊断能否作为"第二次阅片者"还没有被证明。乳腺摄片的计算机辅助诊断技术在乳腺癌诊断中具有重要价值,住院医师和放射科医师都将从中受益。 Breast cancer is globally a major threat for women's health. Early detection, diagnosis and treatment are essential to reducing the mortality. Human second reading of screening mammograms can increase breast cancer detection rates. Overall, both the use of the data source for evaluation of mammography computer-aided detection systems and the application of statistical evaluation methods were found highly diverse, so results reported from different studies are hardly comparable. Whereas this has not been proven for current computer-aided detection systems as "second reader". Computeraided diagnosis technique is of much value in assessing the breast malignancy, residents or radiologists seem to benefit from computer-aided detection systems.
出处 《医学与哲学(B)》 2013年第3期59-62,共4页 Medicine & Philosophy(B)
关键词 计算机辅助诊断 乳腺癌 乳腺摄片 diagnosis computer-assisted breast neoplasm mammography
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参考文献33

  • 1赵洪斌,刘丹.CAD技术在乳腺癌诊断中的应用研究[J].中国民康医学,2011,23(6):769-770. 被引量:2
  • 2童振,蒲立新,曲建明.基于乳腺X线成像的计算机辅助诊断技术研究进展[J].中国数字医学,2011,6(2):98-101. 被引量:2
  • 3车琳琳,张光玉,宋莉,曹卫芳.基于钼靶X线影像的乳腺微钙化点良恶性识别算法研究[J].中国医学物理学杂志,2011,28(2):2467-2470. 被引量:6
  • 4Horsch A, Hapfelmeier A,Elter M. Needs assessment for next gen-eration computer — aided mammography reference image databasesand evaluation studies[J]. Int J Comput Assist Radiol Surg,2011,6(6):749-767.
  • 5Vibert J F, Valleron A J. The retina as a neuromimetic model to ex-tract data in noisy images : application to detection of microcalcifi-cation clusters in mammography [ J ]. AMIA Annu Symp Proc,2003,2003:684 — 688.
  • 6Yuan X, Shi P. Microcalcification detection based on localized tex-ture comparison[J], Image Processing,2004 ?5 : 2953-2956.
  • 7Altrichter M, Ludanyi Z,Horvath G. Joint analysis of multiplemammographic views in CAD systems for breast cancer detection[J]. Lecture Notes in Computer Science?2005 ,3540 : 760 — 769.
  • 8Kurdziel M,Boryczko K,Yuen D A. Detecting clusters of microcal-cifications in high — resolution mammograms using supportvectormachines[j]. Bio Algorithms Med Syst’2007,3(6): 11 — 21.
  • 9Regentova E,Zhang L, Zheng J, et al. Microcalcification detectionbased on wavelet domain hidden markov tree model:study for inclu-sion to computer aided diagnostic prompting system[J]. Med Phys,2007,34(6):2206-2219.
  • 10Eltonsy N H,Tourassi G D,Elmaghraby A S. A concentric mor-phology model for the detection of masses in mammography [ J ].IEEE Trans Med Imaging,2007,26(6) :880 —889.

二级参考文献97

  • 1叶兆祥,宋秀宇,肖建宇.CT灌注成像在乳腺良、恶性病变诊断中的应用[J].中华放射学杂志,2005,39(10):1050-1054. 被引量:44
  • 2王颀,杨剑敏.乳腺癌的现代诊断方法及其评价[J].中华肿瘤防治杂志,2006,13(3). 被引量:21
  • 3唐健,沈海林.乳腺癌的CT诊断和鉴别诊断[J].苏州大学学报(医学版),2006,26(3):526-527. 被引量:5
  • 4李树玲.乳癌早期发现的意义及要领[J].中国实用外科杂志,1996,16(4):196-196.
  • 5[3]CHRISTINE L TSIEN, ISAAC S KOHANE, NEIL MCLNTOSH. Multiple signal integration by decision tree induction to detect artifacts in the neonatal intensive care unit[J]. Artificial Intelligence in Medicine, 2000, 19: 189-202.
  • 6[4]YOUNG MOON CHAE, SEUNG HEE HO. Data mining approach to policy analysis in a health insurance domain[J]. International Journal of Medical Informatics, 2001, 62: 103-111.
  • 7[5]JIEWEI HAN,MICHELINE KAMBER.数据挖掘:概念与技术[M].范明译.北京:机械工业出版社,2001.
  • 8[6]WILLIAM H WOLBERG, MANASARIAN O L. Multisurface method of pattern separation for medical diagnosis applied to breast cytology [J]. Proceedings of the National Academy of Sciences, 1990, 87: 9193-9196.
  • 9[7]MANGASARIAN O L, SETIONO R, WOLBERG W H. Pattern recognition via linear programming: Theory and application to medical diagnosis[A]. Proceedings of the Workshop on Large-Scale Numerical Optimization[C]. Philadelphia: SIAM Publications, 1990. 22-31.
  • 10Rangayyan RM,Ayres FJ,Desautels JEL.A review of computer-aided diagnosis of breast cancer: Toward the detection of early signs[J] J.Franklin Inst.,2007,344(3/4): 312-348.

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