Automatic Liver Segmentation in Abdomen CT Images using SLIC and AdaBoost Algorithms

Abstract

This study is an implementation of liver segmentation on abdomen CT images. The liver organ was segmented by using SLIC super-pixel and AdaBoost algorithms. Firstly, the images were clustered by SLIC super-pixel algorithm. Then, the liver was segmented by AdaBoost classifier. The segmentation process was done automatically. The automatic segmentation is based on the classification of overlapping patches of the image. The results of automatic segmentation and manual segmentation were compared and the efficiency of the method was observed. The best Dice rate was obtained as 92.13% and the best Jaccard rate was obtained as 85.8% on 16 abdomen CT images.