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基于3D区域增长法和改进的凸包算法相结合的全肺分割方法

代双凤 吕科 翟锐 董继阳

代双凤, 吕科, 翟锐, 董继阳. 基于3D区域增长法和改进的凸包算法相结合的全肺分割方法[J]. 电子与信息学报, 2016, 38(9): 2358-2364. doi: 10.11999/JEIT151365
引用本文: 代双凤, 吕科, 翟锐, 董继阳. 基于3D区域增长法和改进的凸包算法相结合的全肺分割方法[J]. 电子与信息学报, 2016, 38(9): 2358-2364. doi: 10.11999/JEIT151365
DAI Shuangfeng, Lü Ke, ZHAI Rui, DONG Jiyang. Lung Segmentation Method Based on 3D Region Growing Method and Improved Convex Hull Algorithm[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2358-2364. doi: 10.11999/JEIT151365
Citation: DAI Shuangfeng, Lü Ke, ZHAI Rui, DONG Jiyang. Lung Segmentation Method Based on 3D Region Growing Method and Improved Convex Hull Algorithm[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2358-2364. doi: 10.11999/JEIT151365

基于3D区域增长法和改进的凸包算法相结合的全肺分割方法

doi: 10.11999/JEIT151365
基金项目: 

国家自然科学基金(U1301251, 61271435),北京市自然科学基金(4141003)

Lung Segmentation Method Based on 3D Region Growing Method and Improved Convex Hull Algorithm

Funds: 

The National Natural Science Foundation of China (U1301251, 61271435), Beijing Natural Science Foundation (4141003)

  • 摘要: 肺实质分割结果的准确性在实际临床应用中具有非常重要的意义。但由于肺结节的位置、大小、形状的不规则性,肺部病变的多样性,以及人体胸部解剖结构的明显差异等,使得各类分割方法不能统一地适用于所有的胸部CT图像,所以对于肺实质分割方法的研究仍具有很大的挑战。该文在国内外研究分析的基础上提出基于3D区域增长法与改进的凸包修补算法相结合的全肺分割方法。在3D区域增长法的粗分割基础上,对分割的结果进行细化工作,通过连通域标记法与形态学方法相结合去除气管和主支气管,得到初步的肺实质掩膜,最后应用改进的凸包算法对肺部轮廓进行修补平滑,最终得到肺部分割结果。通过与凸包算法及滚球法相对比,证明该文所提改进的凸包算法能够有效地修补肺部轮廓凹陷,修补后的结果分割精度较高。
  • MANSOOR A, BAGCI U, XU Z, et al. A generic approach to pathological lung segmentation[J]. IEEE Transactions on Medical Imaging, 2014, 33(12): 2293-2310. doi: 10.1109/TMI. 2014.2384693.
    王娜娜, 陈树越. 基于CT图像的肺实质分割技术研究[J]. 电子测试, 2012(4): 38-43. doi: 10.3969/j.issn.1000-8519.2012. 04.009.
    WANG Nana and CHEN Shuyue. Research progress of lung parenchyma segmentation techniques based on CT images [J]. Electronic Test. 2012(4): 38-43. doi: 10.3969/j.issn.1000- 8519.2012.04.009.
    陈琪, 熊博莅, 陆军, 等. 改进的二维Otsu图像分割方法及其快速实现[J]. 电子与信息学报, 2010, 32(5): 1100-1104. doi: 10.3724/SP.J.1146.2009.00627.
    CHEN Qi, XIONG Boli, LU Jun, et al. Improved two- dimensional Otsu image segmentation method and fast recursive realization[J]. Journal of Electronics Information Technology, 2010, 32(5): 1100-1104. doi: 10.3724/SP.J.1146. 2009.00627.
    贾同, 孟琭, 赵大哲, 等. 基于CT 图像的自动肺实质分割方法[J]. 东北大学学报(自然科学版), 2008, 29(7): 965-968. doi: 10.3321/j. issn:1005-3026.2008.07.014.
    JIA Tong, MENG Lu, ZHAO Dazhe, et al. Automatic lung parenchyma segmentation on CT image[J]. Journal of Northeastern University (Natural Science), 2008, 29(7): 965-968. doi: 10.3321/j. issn:1005-3026.2008.07.014.
    杨建峰, 赵涓涓, 强彦, 等. 结合区域生长的多尺度分水岭算法的肺分割[J]. 计算机工程与设计, 2014, 35(1): 213-217. doi: 10.3969/j.issn.1000-7024.2014.01.040.
    YANG Jianfeng, ZHAO Juanjuan, QIANG Yan, et al. Lung CT Image segmentation combined multi-scale watershed method and region growing method[J]. Computer Engineering and Design, 2014, 35(1): 213-217. doi: 10.3969/ j.issn.1000-7024.2014.01.040.
    QIAN Y and WEI G. Lung nodule segmentation using EM algorithm[C]. Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics, Hangzhou, 2014: 20-23.
    刘嘉, 王宏琦. 一种基于图割的交互式图像分割方法[J]. 电子与信息学报, 2008, 30(8): 1973-1976.
    LIU Jia and WANG Hongqi. A graph cuts based interactive image segmentation method[J]. Journal of Electronics Information Technology, 2008, 30(8): 1973-1976.
    DAI S, LU K, DONG J, et al. A novel approach of lung segmentation on chest CT images using graph cuts[J]. Neurocomputing, 2015, 168: 799-807. doi: 10.1016/j.neucom. 2015.05.044.
    卞晓月, 武妍. 基于CT图像的肺实质细分割综合方法[J]. 重庆邮电大学学报(自然科学版), 2010, 22(5): 665-668. doi: 10.3979/j.issn.1673-825X.2010.05.028.
    BIAN Xiaoyue and WU Yan. A method of careful lung segmentation based on CT images[J]. Journal of Chongqing University of Posts and Telecommunications (Natural Science Edition), 2010, 22(5): 665-668. doi: 10.3979/j.issn. 1673-825X.2010.05.028.
    SUDHA V and JAYASHREE P. Lung nodule detection in CT images using thresholding and morphological operations[J]. International Journal of Emerging Science and Engineering (IJESE), 2012, 1(2): 17-21.
    张欣, 王兵, 杨颖, 等. 胸部CT图像肺区域边界凹陷自动修补[J]. 计算机工程与应用, 2013, 49(24): 191-194. doi: 10. 3778/j.issn.1002-8331.1202-0377.
    ZHANG Xin, WANG Bing, YANG Ying, et al. Automatic repair of lung boundary concave in chest CT images[J]. Computer Engineering and Applications, 2013, 49(24): 191-194. doi: 10.3778/j.issn.1002-8331.1202-0377.
    ZHOU S, CHENG Y, and Tamura S. Automated lung segmentation and smoothing techniques for inclusion of juxtapleural nodules and pulmonary vessels on chest CT images[J]. Biomedical Signal Processing and Control, 2014, 13: 62-70. doi: 10.1016/j.bspc.2014.03.010.
    龚敬, 王丽嘉, 王远军. 基于灰度积分投影与模糊C均值聚类的肺实质分割[J]. 中国生物医学工程学报, 2015, 34(1): 109-113. doi: 10.3969/j.issn.0258-8021.2015.01.015.
    GONG Jing, WANG Lijia, and WANG Yuanjun. Segmentation of lung parenchyma based on gray-level integrated projection and fuzzy C-Means clustering algorithm[J]. Chinese Journal of Biomedical Engineering, 2015, 34(1): 109-113. doi: 10.3969/j.issn.0258-8021.2015. 01.015.
    WEI Y, SHEN G, and LI J. A fully automatic method for lung parenchyma segmentation and repairing[J]. Journal of Digital Imaging, 2013, 26(3): 483-495. doi: 10.1007/s10278- 012-9528-9.
    李金, 郑冰, 梁洪, 等. 基于改进凸包算法的肺实质分割研究[J]. 中国生物医学工程学报, 2013, 32(4): 484-490. doi: 10.3969/j.issn.0258-8021.2013.04.015.
    LI Jin, ZHENG Bing, LIANG Hong, et al. Segmentation research of pulmonary parenchyma based on improved convex hull algorithm[J]. Chinese Journal of Biomedical Engineering, 2013, 32(4): 484-490. doi: 10.3969/j.issn.0258-8021.2013. 04.015.
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出版历程
  • 收稿日期:  2015-12-03
  • 修回日期:  2016-05-10
  • 刊出日期:  2016-09-19

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