Multiorgan Segmentation Using Coherent Propagating Level Set Method Guided by Hierarchical Shape Priors and Local Phase Information

In this chapter, we introduce an automatic multiorgan segmentation method using a hierarchical-shape-prior-guided level set method. The hierarchical shape priors are organized according to the anatomical hierarchy of the human body, so that the children structures are always contained by the parent structure. This hierarchical approach solves two challenges of multiorgan segmentation. First, it gradually refines the prediction of the organs’ position by locating and segmenting the larger parent structure. Second, it solves the ambiguity of boundary between two attaching organs by looking at a large scale and imposing the additional shape constraint of the higher-level structures. To improve the segmentation accuracy, a model-guided local phase term is introduced and integrated with the conventional region-based energy function to guide the level set propagation. Finally, a novel coherent propagation method is implemented to speed up the model-based level set segmentation. In theVISCERALAnatomy challenge, the proposedmethod delivered promising results on a number of abdominal organs. C. Wang (B) · Ö. Smedby Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden e-mail: [email protected] Ö. Smedby e-mail: [email protected] C. Wang · Ö. Smedby Department of Radiology and Department of Medical and Health Sciences, Linköping University, Linköping, Sweden C. Wang · Ö. Smedby School of Technology and Health (STH), KTH Royal Institute of Technology, Stockholm, Sweden © The Author(s) 2017 A. Hanbury et al. (eds.), Cloud-Based Benchmarking of Medical Image Analysis, DOI 10.1007/978-3-319-49644-3_10 165 166 C. Wang and Ö. Smedby