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Proceedings Paper

Pulmonary lobe segmentation using the thin plate spline (TPS) with the help of the fissure localization areas
Author(s): Benjamin Odry; Pauline Steininger; Li Zhang; Atilla Kiraly; Alexander Mahnke; Sandra Sudarsky; Carol Novak; Bernhard Geiger; Shuping Qing; Hendrik Ditt
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Paper Abstract

Lung lobe segmentation is clinically important for disease classification, treatment and follow-up of pulmonary diseases. Diseases such as tuberculosis and silicolis typically present in specific lobes i.e. almost exclusively the upper ones. However, the fissures separating different lobes are often difficult to detect because of their variable shape, appearance and low contrast in computed tomography images. In addition, a substantial fraction of patients have missing or incomplete fissures. To solve this problem, several methods have been employed to interpolate incomplete or missed fissures. For example, Pu et al. used an implicit surface fitting with different radial basis functions; Ukil et al. apply fast marching methods; and Ross et al. used an interactive thin plate spline (TPS) interpolation where the user selects the points that will be used to compute the fissure interpolation via TPS. In our study, results of an automated fissure detection method based on a plate-filter as well points derived from vessels were fed into an a robust TPS interpolation that ultimately defined the lobes. To improve the selection of detected points, we statistically determined the areas where fissures are localized from 19 data-sets. These areas were also used to constrain TPS fitting so it reflected the expected shape and orientation of the fissures, hence improving result accuracy. Regions where the detection step provided low response were replaced by points derived from a distance-to-vessels map. The error, defined as the Euclidian mean distance between ground truth points and the TPS fitted fissures, was computed for each dataset to validate our results. Ground truth points were defined for both exact fissure locations and approximate fissure locations (when the fissures were not clearly visible). The mean error was 5.64±4.83 mm for the exact ground truth points, and 10.01 ± 8.23 mm for the approximate ground truth points.

Paper Details

Date Published: 13 March 2013
PDF: 11 pages
Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86690X (13 March 2013); doi: 10.1117/12.2007098
Show Author Affiliations
Benjamin Odry, Siemens Corporate Technology (United States)
Pauline Steininger, Siemens Corporate Technology (United States)
Li Zhang, Siemens Corporate Technology (United States)
Atilla Kiraly, Siemens Corporate Technology (United States)
Alexander Mahnke, Siemens AG (Germany)
Sandra Sudarsky, Siemens Corporate Technology (United States)
Carol Novak, Siemens Corporate Technology (United States)
Bernhard Geiger, Siemens Corporate Technology (United States)
Shuping Qing, Siemens Corporate Technology (United States)
Hendrik Ditt, Siemens AG (Germany)


Published in SPIE Proceedings Vol. 8669:
Medical Imaging 2013: Image Processing
Sebastien Ourselin; David R. Haynor, Editor(s)

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