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L. Zhang, E. A. Hoffman, and J. M. Reinhardt. Lung lobar segmentation by graph search with 3D shape constraints. In C.-T. Chen and A. V. Clough, eds., Proc. SPIE Conf. Medical Imaging, vol. 4321, pp. 204-215, San Diego, CA, 2001.

Abstract: The lung lobes are natural units for reporting image-based measurements of the respiratory system. Lobar segmentation can also be used in pulmonary image processing to guide registration and drive additional segmentation. We have developed a 3D shape-constrained lobar segmentation technique for volumetric pulmonary CT images. The method consists of a search engine and shape constraints that work together to detect lobar fissures using gray level information and anatomic shape characteristics in two steps: 1) a coarse localization step, 2) a fine tuning step. An error detecting mechanism using shape constraints is used in our method to correct erroneous search results. Our method has been tested in four subjects, and the results are compared to manually traced results. The average RMS difference between the manual results and shape-constrained segmentation results is 2.23 mm. We further validated our method by evaluating the repeatability of lobar volumes measured from repeat scans of the same subject. We compared lobar air and tissue volume variations to show that most of the lobar volume variations are due to differences in air volume scan to scan.

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Keywords: lobes segmentation

Other publications by: L. Zhang, E. A. Hoffman, J. M. Reinhardt

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L. Zhang, E. A. Hoffman, and J. M. Reinhardt. Lung lobe segmentation in volumetric X-ray CT images. IEEE Trans. Medical Imaging, vol. 25, no. 1, pp. 1-16, 2006. (details)
S. Ukil and J. M. Reinhardt. Anatomy-guided lung lobar surface detection in X-ray CT images. IEEE Trans. Medical Imaging, vol. 28, no. 2, pp. 202-214, 2009. (details)
J. M. Reinhardt and W. E. Higgins. Paradigm for Shape-Based Image Analysis. Optical Engineering, vol. 37, no. 2, pp. 570-581, 1998. (details)
J. M. Reinhardt, A. J. Wang, T. P. Weldon, and W. E. Higgins. Cue-Based Segmentation of 4D Cardiac Image Sequences. Comp. Vision and Image Understanding, vol. 77, no. 2, pp. 251-262, 2000. (details)
S. Hu, E. A. Hoffman, and J. M. Reinhardt. Automatic lung segmentation for accurate quantitation of volumetric X-ray CT images. IEEE Trans. Medical Imaging, vol. 20, no. 6, pp. 490-498, 2001. (details)

Related conference papers:

L. Zhang and J. M. Reinhardt. Detection of Lung Lobar Fissures using Fuzzy Logic. In Proc. SPIE Conf. Medical Imaging, vol. 3660, pp. 188-199, 1999. (details)
L. Zhang, E. A. Hoffman, and J. M. Reinhardt. Atlas-Driven Lung Lobe Segmentation in Volumetric X-ray CT Images. In M. Sonka and J. M. Fitzpatrick, eds., Proc. SPIE Conf. Medical Imaging, vol. 5032, pp. 309-319, San Diego, CA, 2003. (details)
S. Ukil, E. A. Hoffman, and J. M. Reinhardt. Automatic lung lobe segmentation in X-ray CT images by 3D watershed transform using anatomic information from the segmented airway tree. In J. M. Fitzpatrick and J. M. Reinhardt, eds., Proc. SPIE Conf. Medical Imaging, vol. 5747, pp. 556-567, San Diego, CA, 2005. (details)
S. Ukil, M. Sonka, and J. M. Reinhardt. Automatic segmentation of pulmonary fissures in X-ray CT images using anatomic guidance. In J. M. Reinhardt and J. P. Pluim, eds., Proc. SPIE Conf. Medical Imaging, vol. 6144, pp. 213-223, San Diego, CA, 2006. (details)
W. E. Higgins, W. L. Sharp, M. W. Hansen, and J. M. Reinhardt. A graphical user interface system for 3D medical image analysis. In Y. Kim, ed., Proc. SPIE Conf. Medical Imaging, vol. 2164, Newport Beach, CA, 1994. (details)

Related theses:

S. Ukil. Anatomy-guided lung lobe segmentation and fissure analysis in X-ray CT images. PhD thesis, The University of Iowa, Iowa City, IA, 2006. (details)
L. Zhang. Atlas-driven lung lobe segmentation in volumetric X-ray CT images. PhD thesis, The University of Iowa, Iowa City, IA, 2002. (details)
D. Aykac. Segmentation and analysis of the human airway tree from 3D X-ray CT images. MS thesis, The University of Iowa, Iowa City, IA, 2000. (details)