基于区域增长法的三维支气管树分割算法

计算机科学 ›› 2015, Vol. 42 ›› Issue (Z11): 192-194.

基于区域增长法的三维支气管树分割算法

李艳波,于翔

黑龙江工程学院计算机科学与技术学院哈尔滨150050,黑龙江工程学院计算机科学与技术学院哈尔滨150050

出版日期:2018-11-14 发布日期:2018-11-14
基金资助:
本文受黑龙江省教育厅科研项目(12531539)资助

Three Dimensional Airway Trees Segmentation Algorithm Based on Region Growing Method

LI Yan-bo and YU Xiang

Online:2018-11-14 Published:2018-11-14

摘要/Abstract

摘要： 虚拟内窥镜在胸部疾病诊断方面占据重要的地位,通常支气管树分割方法存在分割结果不准确和分割漏洞问题,因此提出基于区域增长法的支气管树分割算法。首先通过区域增长法进行主干分割,然后对细小分支进行获取,并通过质量评价函数对细小分支进行筛选,删除伪分支。实验结果表明,该支气管树分割法可以简单、有效地提取出完整的肺支气管树,得到包含第5级以上的支气管,解决支气管断裂和分割漏洞现象,具有较好的鲁棒性。

关键词: 虚拟内窥镜,支气管树分割,区域增长法,候选分支,评价函数

Abstract: Virtual bronchoscopy(VB) plays an important role in the evaluation of chest diseases,but as the main key technology,airway tree segmentation method has problems of inaccurate and leakage phenomenon.Therefore,the airway trees segmentation based on region growing method was proposed.Firstly,region growing method is used to extract the main branch.Secondly,it extracts the sub-branch and deletes the pseudo branch according to the quality evaluation function.The experiment results show that the robust airway segmentation method can extract the complete lung airway tree simply,robustly and effectively with magnitude 5 bronchus,which solves the bronchial rupture and segmentation leakage problems.

Key words: Virtual bronchoscopy,Airway trees segmentation,Region growing method,Candidate branch,Evaluation function

李艳波,于翔. 基于区域增长法的三维支气管树分割算法[J]. 计算机科学, 2015, 42(Z11): 192-194. https://doi.org/

LI Yan-bo and YU Xiang. Three Dimensional Airway Trees Segmentation Algorithm Based on Region Growing Method[J]. Computer Science, 2015, 42(Z11): 192-194. https://doi.org/

参考文献

[1] Graham M W,Gibbs J D,Higgins W E.A robust system for human airway tree segmentation[C]∥SPIE Medical Imaging:Ima-ge Processing.2008
[2] Graham M W,Gibbs J D,Higgins W E.Computer based route definition system for peripheral bronchoscopy[J].Journal of digi-tal imaging,2012,5(2):307-317
[3] Kiraly A P,Higgins W E,Hoffman E A,et al.3D human airway segmentation method for virtual bronchoscopy[J].Academic Radiology,2002,9(10):1153-1168
[4] Mori K,Hasegawa J,Suenaga Y,et al.Automated anatomical labeling of the bronchial branch and its application to the virtual bronchoscopy system[J].IEEE Transactions on Medical Imaging,2000,19(2):103-104
[5] Suter M,Schirren J T,Reinhardt J,et al.Evaluation of the human airway with multidetector X-ray-computed tomography and optical imaging[J].Physioligical Measurement,2004,25:837-847
[6] Schirren J T,Hoffman E A,Mclennan G,et al.Intrathoracic airway trees:segmentation and airway morphology analysis from low-dose CT scans[J].IEEE Transactions on Medical Imaging,2005,24(12):1529-1539
[7] Gibbs J D.Three dimensional route planning for medical image reporting and endoscopic guidance[D].The Pennsylvania State:The Pennsylvania State University,2008
[8] Graham M W,Gibbs J D,Cornish D C,et al.Robust 3D airway tree segmentation for image-guided peripheral bronchoscopy[J].IEEE Transaction On Medical Imaging,2010,29(4):982-990
[9] Tan Wen-jun,Yang Jin-zhu,Zhao Da-zhe,et al.A Novel Method for Automated Segmentation of Airway Tree[C]∥24th Chinese Control and Decision Conference.2012:976-979

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed