Publication Detail Page

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.

Abstract: The pulmonary lobes are the five distinct anatomic divisions of the human lungs. 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 early detection of pathologies, and also for the regional functional analysis of the lungs. We have developed a two-step automatic method for the accurate segmentation of the three pulmonary fissures. In the first step, an approximation of the actual fissure locations is made using a 3-D watershed transform on the distance map of the segmented vasculature. Information from the anatomically labeled human airway tree is used to guide the watershed segmentation. These approximate fissure boundaries are then used to define the region of interest (ROI) for a more exact 3-D graph search to locate the fissures. Within the ROI the fissures are enhanced by computing a ridgeness measure, and this is used as the cost function for the graph search. The fissures are detected as the optimal surface within the graph defined by the cost function, which is computed by transforming the problem to the problem of finding a minimum s-t cut on a derived graph. The accuracy of the lobar borders is assessed by comparing the automatic results to manually traced lobe segments. The mean distance error between manually traced and computer detected left oblique, right oblique and right horizontal fissures is 2.3 +/- 0.8 mm, 2.3 +/- 0.7 mm and 1.0 +/- 0.1 mm, respectively.

DOI link for this publication

Citation: BibTeX format Endnote format

Keywords: lobes lung segmentation

Other publications by: S. Ukil, M. Sonka, J. M. Reinhardt

Related journal papers:

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)
S. Ukil and J. M. Reinhardt. Smoothing Lung Segmentation Surfaces in 3D X-ray CT Images using Anatomic Guidance. Acad. Radiol., vol. 12, no. 12, pp. 1502-1511, 2005. (details)
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)

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)
B. Li and J. M. Reinhardt. Automatic generation of 3-D shape models and their application to tomographic image segmentation. In M. Sonka and K. M. Hansen, eds., Proc. SPIE Conf. Medical Imaging, vol. 4322, pp. 311-322, San Diego, CA, 2001. (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)
L. Shi, E. A. Hoffman, and J. M. Reinhardt. Segmentation of the Ovine Lung in 3D CT Images. In A. Amini and A. Manduca, eds., Proc. SPIE Conf. Medical Imaging, vol. 5369, pp. 455-463, San Diego, CA, 2004. (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)
K. Ding. Registration-based regional lung mechanical analysis. MS thesis, The University of Iowa, Iowa City, IA, 2008. (details)
B. Li. The construction of a normative human lung atlas by inter-subject registration and warping of CT images. PhD thesis, The University of Iowa, Iowa City, IA, 2004. (details)