No abstract

In this paper we present an automatic volumetric liver localization method as an approach for liver segmentation. In the proposed method the aim is to localise a mean shape model of the liver in the target CT scan. The framework consists of three main steps: shape model construction, low level processing and shape model registration. We evaluated our method on the MICCAI 2007 liver segmentation challenge dataset. The Leaveone-out validation results demonstrate the effectiveness of the proposed method. The average volume overlap between our method and the ground truth, using the Jaccard index, is 0.64±0.11 which is acceptable for an initial localisation of the liver prior to further refinement.