LAUSR

This letter introduces a unified framework for accurate segmentation of five different types of pulmonary nodules, namely, solid, juxtapleural, juxtavascular, part solid and ground glass by designing a contrast-adaptive shape-driven level set algorithm. Most of the existing methods have targeted segmenting few specific types of nodules. Variability of shapes along with poor contrast make pulmonary nodule segmentation an extremely challenging problem. To deal with low contrast, a contrast-adaptive term, based on intensities, is incorporated to guide the evolution of level set. A shape term is further introduced for accurate segmentation of different pulmonary nodules having varying shapes. Experiments on the publicly available LIDC/IDRI dataset clearly reveal that our method achieves promising results as compared to several state-of-the-art competitors.