A New Lung Segmentation Algorithm for Pathological CT Images

This paper presents a new lung segmentation algorithm which is based on anatomical knowledge and Snake model. This algorithm totally overcomes the disadvantage of traditional lung segmentation algorithms, which are mainly based on edge extraction, mathematical morphology, region growing, threshold, etc.; and can´t get satisfied results when segmenting pathological clinical CT images with traditional algorithms. Experiments showed that no matter whether the CT images are pathological or not, this segmentation algorithm has good results, high speed, and total automation.