一种三维规则数据场中复杂组织快速分割方法  

Tissue segmentation based on 3D morphology and 3D seed filling

作　　者：李文岗[1] 薛斌党[2] 姜志国[2] 

机构地区：[1]福建医科大学附属厦门第一医院肝胆胰血管外科,厦门361003 [2]北京航空航天大学宇航学院图像中心,北京100083

出　　处：《中国体视学与图像分析》2008年第2期106-110,共5页Chinese Journal of Stereology and Image Analysis

基　　金：国家自然科学基金项目(No.60502018);厦门市科委基金项目(No.3502Z20064011)

摘　　要：提出了一种三维规则数据场中复杂组织快速分割方法:首先熵阈值二值化三维医学图像,然后用三维形态学腐蚀操作,断开复杂组织与其它组织间的弱连接,并对复杂组织进行连通标记;接着提取出腐蚀后的复杂组织模板,并对此模板进行三维形态学扩张操作,恢复先前三维形态学腐蚀操作消除的部分;最后采用改进的快速三维种子填充算法精确地分割出复杂组织。复杂组织分割实验结果表明了该方法的有效性。A method based on 3D mathematical morphology theory and 3D seed filling algorithm is present for the segmentation of complicated tissue. Firstly, two thresholds were chosen to make the original 3D regular data set to be binary dataset ; Secondly, the 3 D mathematical morphology erosion operator was applied to cut off the weak linkage relation between the complicated tissue and other tissues, and the adjacent connection relationship of the voxel （volume element） in the complicated tissue was labeled, then the complicated tissue template was extracted. Thirdly, the 3 D mathematical morphology dilation operator was applied to the extracted tissue template to recover the tissue from the erosion template. Finally, an improved effective 3D seed fill algorithm was proposed to obtain the accurate complicated tissue. Experimental results show that the segmentation method is effective.

关 键 词：三维组织分割 三维规则数据场 三维形态学 三维种子填充 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]