三维CB数学形态学在肝脏CT图像分割中的应用

Applications of 3D CB mathematical morphology in liver CT image series segmentation

提出了一种基于三维CB数学形态学的CT图像中肝脏三维交互分割方法:二值化三维医学图像后用三维CB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;随后提取出腐蚀后的复杂组织模板,并对此模板进行三维CB形态学扩张操作,恢复先前三维CB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分割出复杂组织。肝脏CT图像中复杂组织三维分割实验结果证明了该算法的有效性。

An interactive 3D segmentation method based on 3D CB mathematical morphology for extracting complex tissues from liver CT image series is presented.Firstly,two thresholds were chosen to make the original 3D regular data set into binary dataset.Secondly,the 3D CB mathematical morphology erosion operator was applied to cut off the weak linkage relation between the complicated tissue from 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 3D CB mathematical morphology dilation operator was applied to the extracted tissue template to recover the tissue from the erosion template.Finally,an improved 3D seed fill algorithm was used to extract the complicated tissue.Experimental results have demonstrated the effectiveness of this segmentation method.