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Proceedings Paper

Lung lobe segmentation by graph search with 3D shape constraints
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Paper Abstract

The lung lobes are natural units for reporting image-based measurements of the respiratory system. Lobar segmentation can also be used in pulmonary image processing to guide registration and drive additional segmentation. We have developed a 3D shape-constrained lobar segmentation technique for volumetric pulmonary CT images. The method consists of a search engine and shape constraints that work together to detect lobar fissures using gray level information and anatomic shape characteristics in two steps: (1) a coarse localization step, (2) a fine tuning step. An error detecting mechanism using shape constraints is used in our method to correct erroneous search results. Our method has been tested in four subjects, and the results are compared to manually traced results. The average RMS difference between the manual results and shape-constrained segmentation results is 2.23 mm. We further validated our method by evaluating the repeatability of lobar volumes measured from repeat scans of the same subject. We compared lobar air and tissue volume variations to show that most of the lobar volume variations are due to difference in air volume scan to scan.

Paper Details

Date Published: 21 May 2001
PDF: 12 pages
Proc. SPIE 4321, Medical Imaging 2001: Physiology and Function from Multidimensional Images, (21 May 2001); doi: 10.1117/12.428138
Show Author Affiliations
Li Zhang, Univ. of Iowa (United States)
Eric A. Hoffman, Univ. of Iowa (United States)
Joseph M. Reinhardt, Univ. of Iowa (United States)

Published in SPIE Proceedings Vol. 4321:
Medical Imaging 2001: Physiology and Function from Multidimensional Images
Chin-Tu Chen; Anne V. Clough, Editor(s)

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