3D lung segmentation of the CT series based on 2D Chan-Vese

This paper presents a new 3D segmentation algorithm for lung segmentation tasks on CT series. The algorithm consists of a 2D stage (for each slice) which is performed parallelly and 3D postprocessing after merging to 3D. The 2D stage consists of 2D preprocessing, Chan - Vese segmentation, and 2D postprocessing. This algorithm was tested on the set of 60 CT series containing labelled data enable to its assessment. The results of the algorithm are close to deep learning approaches. This algorithm will be an element of a commercial expert system for medical applications where some patient assessment will be necessary based on segmented human organs.