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

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)

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- 被引次数: 0
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

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

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。
- 肺部分割 /
- 3D区域增长法 /
- 凸包算法 /
- 区域连通分析
Abstract: The accuracy of lung segmented results is important in actual clinical application. However, all kinds of segmentation methods can not be uniform for all the chest CT (Computed Tomography) images because of the irregularities and diversity of lung disease, as well as significant differences in the anatomy of the human chest. Lung parenchyma segmentation studies still have a great challenge. Based on the analysis of domestic and international research, a new lung segmentation method is presented by combining with 3D region growing method and improved convex hull patching algorithm. Firstly, the 3D region growing method is adopted for the rough segmentation of lung CT images. Then the refining work is done to the segmented results. The connected domain labeling and morphological methods are used to remove the trachea and main bronchi to get the pulmonary parenchyma mask. The improved convex hull algorithm is presented to repair and smooth the concavities of lung contour. Finally, the segmented results can be gotten. The improved convex hull algorithm can repair the concavities of lung contour effectively in comparison with the convex hull algorithm and the rolling ball method, and the segmentation precision of results is very high after repairing.
- Lung segmentation /
- 3D region growing method /
- Convex hull algorithm /
- Connected domain processing

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参考文献(24)

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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