Computer Science ›› 2016, Vol. 43 ›› Issue (Z11): 193-196.doi: 10.11896/j.issn.1002-137X.2016.11A.043

Previous Articles     Next Articles

Level Set Medical Image Segmentation Method Combining Watershed Algorithm

ZHANG Hui, ZHU Jia-ming, CHEN Jing and WU Jie   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Complex targets of medical image are usually difficult to be completely segmented,so an image segmentation algorithm of modified Li model combining mark watershed algorithm was proposed.A symbol pressure function replaces the traditional stop function in Modified Li model,and the problem of unidirectional curve evolution is solved.Mark watershed has both stronger ability to suppress noise and stronger ability to capture weak edge of medical image.Firstly,mark watershed algorithm is used for image segmentation pretreatment,positioning information of target edge fast and accurately.Then,the modified Li model algorithm is introduced,and the symbol pressure function is used to guide curve evolution direction and control the size of the evolution speed,realizing full segmentation of complex object.The experimental results show that global information and edge information can be gooten,and the combination algorithm of complex targets can get satisfactory effect in the medical image segmentation.

Key words: Medical image segmentation,Mark watershed,Modified Li model,Sign pressure function

[1] 江贵平,秦文健,周寿军,等.医学图像分割及其发展现状[J].计算机学报,2015,8(6):1222-1241
[2] 刁智华,赵春江,郭新宇,等.分水岭算法的改进方法研究[J].计算机工程,2010,6(17):4-6
[3] Osher S,Sethian J A.Fronts propagating with curvature dependent speed:Algorithms based on the Hamilton-Jacobi formulation [J].Journal of Computational Physics,1998,79:12-49
[4] Li C M,Kao C Y,Gore J C,et al.Minimization of region-scalable fitting energy for image segmentation [J].IEEE Trans on pattern Analysis and Machine Intelligence,2008,7(10):1940-1949
[5] Li C,Xu C,Gui C,et al.Level set evolution without re-initialization:A new variational formulation[C]∥IEEE Conference on Computer Vision and Patten Recognition(CVPR).2005:430-436
[6] Vincent L,Soilh P.Watersheds in digital space:An efficient algorithm based on immersion simulations [J].IEEE Translations on Pattern Analysis and Machine Interpretation,1991,13(6):583-598
[7] 阮秋琦,阮宇智,等.数字图像处理[M].北京:电子工业出版社,2011:497-502
[8] 赵珊,王水.结合进化规划的图像分水岭分割技术[J].计算机科学,2011,38(5):265-267
[9] 方江雄.变分和偏微分方法在图像分割中的应用[M].北京:中国石化出版社,2015:20-23
[10] Xu C Y,Yezzi A,Prince J L.On the relationship between parametric and geometric active contour[C]∥Processing of 34th Asilomar Conference on Signals Systems and Computer.Pacific Grove:IEEE Press,2000:483-489
[11] Salah M B,Mitiche A,Ayed I B.Multiregion image segmentation by parametric kernel graph cuts[J].IEEE Transactions on Image Processing,2011,20(2),545-557
[12] Han X Z,Jian Z.A nonlinear image enhancement algorithmbased on partial differential equations[C]∥IEEE 10th International Conference Signal Processing.2010:1114-1116

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] LEI Li-hui and WANG Jing. Parallelization of LTL Model Checking Based on Possibility Measure[J]. Computer Science, 2018, 45(4): 71 -75, 88 .
[2] XIA Qing-xun and ZHUANG Yi. Remote Attestation Mechanism Based on Locality Principle[J]. Computer Science, 2018, 45(4): 148 -151, 162 .
[3] LI Bai-shen, LI Ling-zhi, SUN Yong and ZHU Yan-qin. Intranet Defense Algorithm Based on Pseudo Boosting Decision Tree[J]. Computer Science, 2018, 45(4): 157 -162 .
[4] WANG Huan, ZHANG Yun-feng and ZHANG Yan. Rapid Decision Method for Repairing Sequence Based on CFDs[J]. Computer Science, 2018, 45(3): 311 -316 .
[5] SUN Qi, JIN Yan, HE Kun and XU Ling-xuan. Hybrid Evolutionary Algorithm for Solving Mixed Capacitated General Routing Problem[J]. Computer Science, 2018, 45(4): 76 -82 .
[6] ZHANG Jia-nan and XIAO Ming-yu. Approximation Algorithm for Weighted Mixed Domination Problem[J]. Computer Science, 2018, 45(4): 83 -88 .
[7] WU Jian-hui, HUANG Zhong-xiang, LI Wu, WU Jian-hui, PENG Xin and ZHANG Sheng. Robustness Optimization of Sequence Decision in Urban Road Construction[J]. Computer Science, 2018, 45(4): 89 -93 .
[8] LIU Qin. Study on Data Quality Based on Constraint in Computer Forensics[J]. Computer Science, 2018, 45(4): 169 -172 .
[9] ZHONG Fei and YANG Bin. License Plate Detection Based on Principal Component Analysis Network[J]. Computer Science, 2018, 45(3): 268 -273 .
[10] SHI Wen-jun, WU Ji-gang and LUO Yu-chun. Fast and Efficient Scheduling Algorithms for Mobile Cloud Offloading[J]. Computer Science, 2018, 45(4): 94 -99, 116 .