RSNA 2009 

Abstract Archives of the RSNA, 2009


SSG17-09

Automatic Segmentation of the Pulmonary Lobes from Computed Tomography Chest CT Scans: Robustness against Incomplete Fissures by Including Contextual Information

Scientific Papers

Presented on December 1, 2009
Presented as part of SSG17: Physics (CAD: Colonography and Other)

Participants

Eva Marjolein Van Rikxoort, Presenter: Nothing to Disclose
Mathias Prokop MD, Abstract Co-Author: Nothing to Disclose
Bartjan De Hoop MD, Abstract Co-Author: Nothing to Disclose
Josien Pluim, Abstract Co-Author: Nothing to Disclose
Bram van Ginneken PhD, Abstract Co-Author: Nothing to Disclose

PURPOSE

To develop and validate a robust technique for automatic extraction of the pulmonary lobes from thoracic CT scans that is not sensitive to the presence of incomplete fissures.

METHOD AND MATERIALS

Volumetric CT scans (Philips Mx8000IDT, 16 x 0.75 mm collimation) were used: 100 scans selected from a lung cancer screening program (30 mAs) that showed substantially incomplete fissures, and 20 scans (100-150 mAs) randomly selected from clinical practice. We propose a multi-atlas approach in which existing lobar segmentations in scans with complete fissures are deformed to unseen test scans in which the fissures, the lungs, and the bronchial tree have been automatically segmented. The key element is a cost function that exploits information from fissures, lung borders, and bronchial tree, in such a way that less reliable information (lungs, airways) is only used when the most reliable information (fissures) is missing. To cope with anatomical variation in lobar shapes, the atlas that is anatomically most similar to the test scan is automatically selected. For quantitative evaluation, the right and left major fissure and the right minor fissure in the 20 clinical scans were automatically segmented. For the 100 scans with incomplete fissures, a human observer indicated whether the lobe segmentation was (1) completely correct, (2) incorrect within 12 mm of the true lobe border, or (3) incorrect further than 12 mm from the true lobe border.

RESULTS

The average distance of the manually segmented lobe borders to the automatic lobe borders was 0.48 mm for the left major fissure, 1.23 mm for the right major fissure, and 1.28 mm for the right minor fissure. The observer scored for the left major fissure 79 lobe border as correct and the other 21 to be within 12 mm. For the right major fissure those numbers were 89 and 11, and for the right minor fissure 76 and 24, respectively.

CONCLUSION

Automatic segmentation of pulmonary lobes in cases with substantially incomplete pulmonary fissures is feasible with a high accuracy.

CLINICAL RELEVANCE/APPLICATION

Automatic segmentation of the pulmonary lobes is essential for quantitative analysis of chest CT scans.

Cite This Abstract

Van Rikxoort, E, Prokop, M, De Hoop, B, Pluim, J, van Ginneken, B, Automatic Segmentation of the Pulmonary Lobes from Computed Tomography Chest CT Scans: Robustness against Incomplete Fissures by Including Contextual Information.  Radiological Society of North America 2009 Scientific Assembly and Annual Meeting, November 29 - December 4, 2009 ,Chicago IL. http://archive.rsna.org/2009/8014720.html