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基于能量最小化的肾脏计算断层扫描图像分割方法

张品 梁艳梅 常胜江 范海伦

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基于能量最小化的肾脏计算断层扫描图像分割方法

张品, 梁艳梅, 常胜江, 范海伦

Kidney segmentation in computed tomography sequences based on energy minimization

Zhang Pin, Liang Yan-Mei, Chang Sheng-Jiang, Fan Hai-Lun
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  • 随着成像技术的不断发展, 医学图像处理在计算机辅助诊断和病变管理中的重要作用日渐突出, 而计算断层扫描序列图像的肾脏组织分割是其中的关键步骤. 本文结合肾脏序列图像的连续性特征, 提出了一种基于活动轮廓和图割方法的能量最小化分割模型来自动分割肾脏组织. 根据相邻切片图像的形状差异与层间距之间的关系, 计算出序列图像中适合图割优化能量函数的最优范围. 能量函数采用测地活动轮廓模型和Chan-Vese模型的综合形式, 兼顾了目标的边界和区域信息. 随后, 利用图割方法优化离散化的能量函数, 驱使活动轮廓逐渐向目标边界靠近, 直至收敛为止. 对30组腹腔序列图像进行了算法测试, 实验表明基于能量最小化的分割方法能够有效地提取出序列图像中的肾脏组织, 其分割结果的平均Dice系数达到了93.7%.
    With the continuous development of medical imaging technology, medical image processing has played an increasingly prominent role in computer-aided diagnosis and disease management. Kidney segmentation in abdominal computed tomography (CT) sequences is a key step. In this paper, combining with the contextual property of renal tissues, a new energy minimization model based on active contour and graph cuts is proposed for kidney extraction in CT sequence. According to the relationship between the shape difference in adjacent slices and corresponding layer thickness, the optimal search range of the contour evolution is calculated for graph cut optimization. The energy function, combining the geodesic active contour with Chan-Vese model, takes into account the boundary and regional information. Then, graph cut methods are used to optimize the discrete energy function and drive the active contour towards object boundaries. Thirty abdominal CT sequences are used to evaluate the accuracy and effectiveness of the proposed algorithm. The experimental results reveal that this approach can extract renal tissues in CT sequences effectively and the average Dice coefficient reaches about 93.7%.
    • 基金项目: 国家自然科学基金(批准号: 11374167)、天津市应用基础与前沿技术研究计划重点项目(批准号: 09JCZDJC18300)和教育部博士点基金(批准号: 20090031110033)资助的课题.
    • Funds: Project supported by the National Natural Science Foundation of China (Grant No. 11374167), the Research Project of Application Basis and Frontier Technology of Tianjin, China (Grant No. 09JCZDJC18300), and the Doctoral Fund of Ministry of Education of China (Grant No. 20090031110033).
    [1]

    Wang L Y, Li L, Yan B, Jiang C S, Wang H Y, Bao S L 2010 Chin. Phys. B 19 088106

    [2]

    Xu Y, Wang W T, Wang W M 2012 Chin. Phys. B 21 118704

    [3]

    Deserno T M, Aach T, Amunts K, Hillen W, Kuhlen T, Scholl I 2011 Comput. Sci. Res. Dev. 26 1

    [4]

    Yao C, Chen H J, Yang Y Y, Li Y F, Han Z Z, Zhang S J 2013 Acta Phys. Sin. 62 088702 (in Chinese) [姚畅, 陈后金, Yang Yong-Yi, 李艳凤, 韩振中, 张胜君 2013 62 088702]

    [5]

    Pham D L, Xu C, Prince J L 2000 Annu. Rev. Biomed. Eng. 2 315

    [6]

    Pohle R, Toennies K D 2001 Image Process. Commun. 7 992113

    [7]

    Lin D T, Lei C C, Hung S W 2006 IEEE Trans. Inf. Technol. Biomed. 10 59

    [8]

    Khalifa F, Gimel’farb G, El-Ghar M A, Sokhadze G, Manning S, McClure P, Ouseph R, El-Baz A 2011 18th IEEE International Conference on Image Processing (ICIP) Brussels, Belgium, September 11-14, 2011 p3393

    [9]

    Gloger O, Tonnies K D, Liebscher V, Kugelmann B, Laqua R, Volzke H 2012 IEEE Trans. Med. Imaging 31 312

    [10]

    Shim H, Chang S, Tao C, Wang J H, Kaya D, Bae K T 2009 J. Comput. Assist Tomogr. 33 893

    [11]

    Freiman M, Kronman A, Esses S J, Joskowicz L, Sosna J 2010 Proceedings of the Medical Image Computing and Computer-Assisted Intervention (MICCAI) Beijing, China, September 20-24, 2010 p73

    [12]

    Boykov Y, Kolmogorov V 2003 Proceedings of International Conference on Computer Vision Nice, France, October 13-16, 2003 p26

    [13]

    Xu N, Ahuja N, Bansal R 2007 Comput. Vis. Image Und. 107 210

    [14]

    El-Zehiry N, Xu S, Sahoo P, Elmaghraby A 2007 The Seventh IASTED International Conference on Visualization, Imaging and Image Processing Palma de Mallorca, Spain, August 29-31, 2007 p182

    [15]

    Tao W 2012 IEEE Trans. Image Process. 21 284

    [16]

    Zhang P, Liang Y M, Chang S J 2013 J. Optoelectron.·Laser 24 602 (in Chinese) [张品, 梁艳梅, 常胜江 2013光电子·激光 24 602]

    [17]

    Chan T F, Vese L A 2001 IEEE Trans. Image Process. 10 266

    [18]

    Caselles V, Kimmel R, Sapiro G 1997 Int. J. Comput. Vision 22 61

    [19]

    Kolmogorov V, Zabih R 2004 IEEE Trans. Pattern Anal. 26 147

    [20]

    Zhao E W, Liang Y M, Fan H L 2013 Opt. Commun. 290 55

    [21]

    Ding M, Chiu B, Gyacskov I, Yuan X, Drangova M, Downey D B, Fenster A 2007 Med. Phys. 34 4109

    [22]

    Zhao E W 2012 M. S. Dissertation (Tianjin: Naikai University) (in Chinese) [赵恩伟 2012 硕士学位论文 (天津: 南开大学)]

    [23]

    Zou K H, Warfield S K, Bharatha A, Tempany C M C, Kaus M R, Haker S J, III W M W, Jolesz F A, Kikinis R 2004 Acad. Radiol. 11 178

  • [1]

    Wang L Y, Li L, Yan B, Jiang C S, Wang H Y, Bao S L 2010 Chin. Phys. B 19 088106

    [2]

    Xu Y, Wang W T, Wang W M 2012 Chin. Phys. B 21 118704

    [3]

    Deserno T M, Aach T, Amunts K, Hillen W, Kuhlen T, Scholl I 2011 Comput. Sci. Res. Dev. 26 1

    [4]

    Yao C, Chen H J, Yang Y Y, Li Y F, Han Z Z, Zhang S J 2013 Acta Phys. Sin. 62 088702 (in Chinese) [姚畅, 陈后金, Yang Yong-Yi, 李艳凤, 韩振中, 张胜君 2013 62 088702]

    [5]

    Pham D L, Xu C, Prince J L 2000 Annu. Rev. Biomed. Eng. 2 315

    [6]

    Pohle R, Toennies K D 2001 Image Process. Commun. 7 992113

    [7]

    Lin D T, Lei C C, Hung S W 2006 IEEE Trans. Inf. Technol. Biomed. 10 59

    [8]

    Khalifa F, Gimel’farb G, El-Ghar M A, Sokhadze G, Manning S, McClure P, Ouseph R, El-Baz A 2011 18th IEEE International Conference on Image Processing (ICIP) Brussels, Belgium, September 11-14, 2011 p3393

    [9]

    Gloger O, Tonnies K D, Liebscher V, Kugelmann B, Laqua R, Volzke H 2012 IEEE Trans. Med. Imaging 31 312

    [10]

    Shim H, Chang S, Tao C, Wang J H, Kaya D, Bae K T 2009 J. Comput. Assist Tomogr. 33 893

    [11]

    Freiman M, Kronman A, Esses S J, Joskowicz L, Sosna J 2010 Proceedings of the Medical Image Computing and Computer-Assisted Intervention (MICCAI) Beijing, China, September 20-24, 2010 p73

    [12]

    Boykov Y, Kolmogorov V 2003 Proceedings of International Conference on Computer Vision Nice, France, October 13-16, 2003 p26

    [13]

    Xu N, Ahuja N, Bansal R 2007 Comput. Vis. Image Und. 107 210

    [14]

    El-Zehiry N, Xu S, Sahoo P, Elmaghraby A 2007 The Seventh IASTED International Conference on Visualization, Imaging and Image Processing Palma de Mallorca, Spain, August 29-31, 2007 p182

    [15]

    Tao W 2012 IEEE Trans. Image Process. 21 284

    [16]

    Zhang P, Liang Y M, Chang S J 2013 J. Optoelectron.·Laser 24 602 (in Chinese) [张品, 梁艳梅, 常胜江 2013光电子·激光 24 602]

    [17]

    Chan T F, Vese L A 2001 IEEE Trans. Image Process. 10 266

    [18]

    Caselles V, Kimmel R, Sapiro G 1997 Int. J. Comput. Vision 22 61

    [19]

    Kolmogorov V, Zabih R 2004 IEEE Trans. Pattern Anal. 26 147

    [20]

    Zhao E W, Liang Y M, Fan H L 2013 Opt. Commun. 290 55

    [21]

    Ding M, Chiu B, Gyacskov I, Yuan X, Drangova M, Downey D B, Fenster A 2007 Med. Phys. 34 4109

    [22]

    Zhao E W 2012 M. S. Dissertation (Tianjin: Naikai University) (in Chinese) [赵恩伟 2012 硕士学位论文 (天津: 南开大学)]

    [23]

    Zou K H, Warfield S K, Bharatha A, Tempany C M C, Kaus M R, Haker S J, III W M W, Jolesz F A, Kikinis R 2004 Acad. Radiol. 11 178

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出版历程
  • 收稿日期:  2013-04-23
  • 修回日期:  2013-07-01
  • 刊出日期:  2013-10-05

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