AUTOMATIC SEGMENTATION OF LUNG LOBES IN CT IMAGES BASED ON FISSURES, VESSELS, AND BRONCHI
Bianca Lassen, Jan-Martin Kuhnigk, Ola Friman, Stefan Krass, Heinz-Otto Peitgen

Lobewise analysis of the pulmonary parenchyma is of clinical relevance for diagnosing and monitoring pathologies. In this work, a fully automatic lobe segmentation approach is presented, which is based on a previously proposed watershed transformation approach. The proposed extension explicitly considers the pulmonary fissures by including them in the cost image for the watershed segmentation. The fissure structures are found through a tailored feature analysis of the Hessian matrix. The method is evaluated using 42 data sets, and a comparison with manual segmentations yields an average volumetric agreement of 96.8%. In comparison to the previously proposed approach, this method increases segmentation accuracy where the fissures are visible.