Incorporating a Local Speed Map in the Levelset Function with Applications in Liver Segmentation

摘要

In this paper, we proposed a method for liver segmentation in CT-scan images that is based on geometric active contours. After reading an input image, we obtain an initial segmentation by an intensity-based technique. Then, we apply a dilation filter on the initial surface to obtain an incremental narrow volume around it. We divide this volume into smaller parts and we prepare the corresponding velocity field in each part individually. The initial surface evolves under the velocity field and this process iterates until convergence. We applied our method on 30 CT-scan datasets including healthy/patient people, and contrast-enhanced/low-contrast images. The average Dice and Jaccard indices were 0.91 and 0.84 respectively. Compared to the STACS algorithm, we improved Dice and Jaccard indices by 0.63 and 0.47.