Automatic Segmentation of the Pulmonary Lobes from Fissures, Airways, and Lung Borders: Evaluation of Robustness against Missing Data

Automatic segmentation of structures with missing or invisible borders is a challenging task. Since structures in the lungs are related, humans use contextual and shape information to infer the position of invisible borders. An example of a task in which the borders are often incomplete or invisible is the segmentation of the pulmonary lobes. In this paper, a fully automatic segmentation of the pulmonary lobes in chest CT scans is presented. The method is especially designed to be robust to incomplete fissures by incorporating contextual information from automatic lung, fissure, and bronchial tree segmentations, as well as shape information. Since the method relies on the result of automatic segmentations, it is important that the method is robust against failure of one or more of these segmentation methods. In an extensive experiment on 10 chest CT scans with manual segmentations, the robustness of the method to incomplete fissures and missing input segmentations is shown. In a second experiment on 100 chest CT scans with incomplete fissures, the method is shown to perform well.

[1]  A. Aziz,et al.  High Resolution CT Anatomy of the Pulmonary Fissures , 2004, Journal of thoracic imaging.

[2]  H. Peitgen,et al.  Informatics in radiology (infoRAD): new tools for computer assistance in thoracic CT. Part 1. Functional analysis of lungs, lung lobes, and bronchopulmonary segments. , 2005, Radiographics : a review publication of the Radiological Society of North America, Inc.

[3]  Joseph M. Reinhardt,et al.  Anatomy-Guided Lung Lobe Segmentation in X-Ray CT Images , 2009, IEEE Transactions on Medical Imaging.

[4]  Bram van Ginneken,et al.  Robust Segmentation and Anatomical Labeling of the Airway Tree from Thoracic CT Scans , 2008, MICCAI.

[5]  Gabor Fichtinger,et al.  Medical Image Computing and Computer-Assisted Intervention - MICCAI 2008, 11th International Conference, New York, NY, USA, September 6-10, 2008, Proceedings, Part I , 2008, International Conference on Medical Image Computing and Computer-Assisted Intervention.

[6]  Eric A. Hoffman,et al.  Atlas-driven lung lobe segmentation in volumetric X-ray CT images , 2006, IEEE Transactions on Medical Imaging.

[7]  B. van Ginneken,et al.  Automatic lung segmentation from thoracic computed tomography scans using a hybrid approach with error detection. , 2009, Medical physics.

[8]  D. Xu,et al.  Nodule management protocol of the NELSON randomised lung cancer screening trial. , 2006, Lung cancer.

[9]  Bram van Ginneken,et al.  Supervised Enhancement Filters: Application to Fissure Detection in Chest CT Scans , 2008, IEEE Transactions on Medical Imaging.