Computer-aided segmentation of pulmonary nodules: Automated vasculature cutoff in thin- and thick-slice CT

Abstract

Consistent volume measurement of pulmonary nodules is essential for follow-up monitoring for diagnosis and therapy purposes. Automated segmentation algorithms have to cope in a robust manner with nodules which are attached to surrounding vessels, the lung walls, or the diaphragm. In this paper we introduce such a nodule segmentation algorithm, and study the effect of slice spacing (thickness) and Hounsfield threshold on the estimated volume. With thin-slice data from multi-array CT scanners, the delicate vasculature structure surrounding most pulmonary nodules becomes visible. Even though the connectivity of the nodules to the surrounding vasculature varies with slice thickness and Hounsfield threshold, we find that the vasculature cutoff decisions of the proposed segmentation algorithm yield consistent measurement characteristics which are robust enough to compare nodule volumes between follow-up CT studies even of different slice thickness. © 2003, Elsevier Science B.V. All rights reserved.