Paper
11 March 2008 Lung lobe modeling and segmentation with individualized surface meshes
Author Affiliations +
Abstract
An automated segmentation of lung lobes in thoracic CT images is of interest for various diagnostic purposes like the quantification of emphysema or the localization of tumors within the lung. Although the separating lung fissures are visible in modern multi-slice CT-scanners, their contrast in the CT-image often does not separate the lobes completely. This makes it impossible to build a reliable segmentation algorithm without additional information. Our approach uses general anatomical knowledge represented in a geometrical mesh model to construct a robust lobe segmentation, which even gives reasonable estimates of lobe volumes if fissures are not visible at all. The paper describes the generation of the lung model mesh including lobes by an average volume model, its adaptation to individual patient data using a special fissure feature image, and a performance evaluation over a test data set showing an average segmentation accuracy of 1 to 3 mm.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thomas Blaffert, Hans Barschdorf, Jens von Berg, Sebastian Dries, Astrid Franz, Tobias Klinder, Cristian Lorenz, Steffen Renisch, and Rafael Wiemker "Lung lobe modeling and segmentation with individualized surface meshes", Proc. SPIE 6914, Medical Imaging 2008: Image Processing, 69141I (11 March 2008); https://doi.org/10.1117/12.770099
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CITATIONS
Cited by 9 scholarly publications.
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KEYWORDS
Lung

Data modeling

Image segmentation

Computed tomography

Fuzzy logic

Image registration

Performance modeling

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