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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.

Abstract: The human lungs are divided into five distinct anatomic compartments called lobes. The physical boundaries between the lobes are called the lobar fissures. Detection of lobar fissure positions in pulmonary X-ray CT images is of increasing interest for the diagnosis of lung disease. We have developed an automatic method for segmentation of all the five lung lobes simultaneously using a 3D watershed transform on a distance transform of a previously generated vessel mask, linearly combined with the original data. Due to the anatomically separate airway sub-trees for individual lobes, we can accurately and automatically place seed points for the watershed segmentation based on the airway tree anatomical description. This, along with seed point placement based on information about the spatial location of the lobes, can give a close approximation to the actual lobar fissures. The accuracy of the lung contours after smoothing is assessed by comparing the automatic results to manually traced transverse slice lobe segments. Averaged over all volumes for all five lobes, the mean similarity index, which is an area overlap measure based on the kappa statistic, is 0.9763 (SD 0.037). The mean RMS distance error between manually traced and automatic oblique fissures is 2.2530 mm (+/- 2.2306 mm SD).

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Keywords: lobes segmentation

Other publications by: S. Ukil, 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)
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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. 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. (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, 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)