Pulmonary lobe segmentation using the thin plate spline (TPS) with the help of the fissure localization areas

Benjamin Odry; Pauline Steininger; Li Zhang; Atilla Kiraly; Alexander Mahnke; Sandra Sudarsky; Carol Novak; Bernhard Geiger; Shuping Qing; Hendrik Ditt

doi:10.1117/12.2007098

13 March 2013 Pulmonary lobe segmentation using the thin plate spline (TPS) with the help of the fissure localization areas

Benjamin Odry, Pauline Steininger, Li Zhang, Atilla Kiraly, Alexander Mahnke, Sandra Sudarsky, Carol Novak, Bernhard Geiger, Shuping Qing, Hendrik Ditt

Author Affiliations +

Proceedings Volume 8669, Medical Imaging 2013: Image Processing; 86690X (2013) https://doi.org/10.1117/12.2007098
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States

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.

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Benjamin Odry, Pauline Steininger, Li Zhang, Atilla Kiraly, Alexander Mahnke, Sandra Sudarsky, Carol Novak, Bernhard Geiger, Shuping Qing, and Hendrik Ditt "Pulmonary lobe segmentation using the thin plate spline (TPS) with the help of the fissure localization areas", Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86690X (13 March 2013); https://doi.org/10.1117/12.2007098

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