We propose an effective technique for the extraction of liver boundary based on multi-planar anatomy and deformable
surface model in abdominal contrast-enhanced CT images. Our method is composed of four main steps. First, for
extracting an optimal volume circumscribing a liver, lower and side boundaries are defined by positional information of
pelvis and rib. An upper boundary is defined by separating the lungs and heart from CT images. Second, for extracting
an initial liver volume, optimal liver volume is smoothed by anisotropic diffusion filtering and is segmented using
adaptively selected threshold value. Third, for removing neighbor organs from initial liver volume, morphological
opening and connected component labeling are applied to multiple planes. Finally, for refining the liver boundaries,
deformable surface model is applied to a posterior liver surface and missing left robe in previous step. Then, probability
summation map is generated by calculating regional information of the segmented liver in coronal plane, which is used
for restoring the inaccurate liver boundaries. Experimental results show that our segmentation method can accurately
extract liver boundaries without leakage to neighbor organs in spite of various liver shape and ambiguous boundary.
|