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一种基于Top-hat的乳腺图像中钙化点的检测方法 被引量:8

A Top-hat Based Calcilfications Detection Method in Mammograms
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摘要 钙化点是乳腺癌早期的一个主要放射学征象。为了实现数字乳腺图像中钙化点的自动检测,提出了一种基于Top-hat算子的钙化点检测方法。该方法采用形态学中的Top-hat算子对图像的背景进行抑制,然后结合孤立钙化点的灰度、纹理和对比度等特征对乳腺图像中的钙化点进行检测。与一般的检测方法相比,这种方法能够有效地检测到强背景中的弱小钙化点目标,而且检测结果贴近于钙化点病灶的真实形状。 Microcalcifications are the primary radiological indicator of early breast cancers. A method for the automatic detection of microcalcifications in digital mammograms is presented in this paper. The algorithm based on top-hat morphologic operator is developed to restrain the background, then the features of single microcalcifications such as gray, texture, and contrast, etc. are extracted to detect the microcalcifications in mammograms. The proposed method is based on the Top-hat operator. Comparing to other approaches, this method can more efficiently detect weak microcaleifications in the high background, and the detected results are much close to the actual shapes of the calcifications.
出处 《中国图象图形学报》 CSCD 北大核心 2006年第12期1839-1843,共5页 Journal of Image and Graphics
基金 教育部重点项目(104173) 新世纪优秀人才支持计划项目(NCET-04-0984)
关键词 TOP-HAT算子 钙化点检测 计算机辅助诊断 Top-hat, detection of calcifications, computer-aided diagnosis
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参考文献9

  • 1章毓晋著.图像工程-图像处理和分析[M].北京:清华大学出版社,1999.
  • 2Wang Ted C,Karayiannis Nicolaos B.Detection of micro-calcifications in digital mammograms using wavelets[J].IEEE Transactions on Medical Imaging,1998,17(4):498~509.
  • 3Gurcan M N,Yardimci Y,Cetin A,et al.Detection of microcalcifications in mammograms using higher order statistics[J].IEEE Signal Processing Letters,1997,4(8):213~216.
  • 4EI-Naqa I,Yang Y,Wernick M,et al.Support vector machine learning for detection of microcalcifications in mammograms[A].In:Proceedings of IEEE International Symposium on Biomedical Imaging[C],Washington,2002:201~204.
  • 5Sorantin E,Schmidt F,Mayer H,et al.Computer aided diagnosis of clustered microcalcifications using artificial neural nets[J].Journal of Computing and Information Technology,2000,8(2):151~160.
  • 6林瑶,田捷,张晓鹏.基于模糊连接度的FCM分割方法在医学图像分析中的应用[J].中国体视学与图像分析,2001,6(2):103-108. 被引量:17
  • 7叶斌,彭嘉雄.基于形态学Top-Hat算子的小目标检测方法[J].中国图象图形学报(A辑),2002,7(7):638-642. 被引量:71
  • 8李斌,彭嘉雄.基于动态规划的红外小目标检测与识别[J].华中理工大学学报,2000,28(6):68-70. 被引量:9
  • 9美国南佛罗里达州立大学.乳腺图像数据库[EB/OL].Http://marathon.csee.usf.edu/Mammography/Database.html,June 2000-06.

二级参考文献12

  • 1彭嘉雄,彭铁.弱目标检测的图像流法[J].红外与激光工程,1996,25(4):34-40. 被引量:28
  • 2N. R. Pal and S. K. Pal, A Review on Image Segmentation Techniques. Pattem Recognition, Vol. 26, No. 9, pp. 1277- 1294,1993.
  • 3James S. Duncan, and Nicholas Ayache, Medical Image Analysis:Progress over Two Decades and the Challenges Ahead, IEEE Transaction on patter analysis and machine intelligence, Vol. 22, No.1, Jan uary 2000.
  • 4S.K. Lee and M.W. Vannier, "Post acquisition correction of MR in homogeneities," Magnetic Resonance Med., Vol. 36, pp. 276 ~ 286,1996.
  • 5D. Pham and J. Prince, "An Adaptive Fuzzy Segmentation Algorithm for Three - Dimensional MRI", Inforrmtion Processing in Medical Imaging, pp. 140~153, 1999.
  • 6J.K. Udupa, and S. Samarasekera, Fuzzy Connectedness and Object Definition: Theory, Algorithms, And Applications in Image Segmentation, Graphical Model and Image Processing, Vol. 58, .No. 3, pp.246~261, 1995.
  • 7A. Rosenfeld, The Fuzzy Geometry of Image Subset, Pattern Recognition Letter 2, pp. 311~317, 1984.
  • 8Anil K.Jain, Robert P.W. Duin and Jian Chang Mao, "Statistical Pattern Recognition: A Review," IEEE Transactions on Pattem Analysis and Machine Intelligence, Vol. 22, No. 1, January 2000.
  • 9Selim S Z, Alsultan K. A Simulated Annealing Algorithm for the Clustering Problem. Pattem Recognition, 1991,24(10): 1003 ~ 1008.
  • 10王浩然,王殊,杨宗凯.子波神经网络在火灾探测中的应用[J].华中理工大学学报,1998,26(11):1-3. 被引量:1

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