We present a pulmonary vessel segmentation algorithm, which is fast, fully automatic and robust. It uses a coarse segmentation of the airway tree and a left and right lung labeled volume to restrict a vessel enhancement filter, based on an offset medialness function, to the lungs. We show the application of our algorithm on contrast-enhanced CT images, where we derive a clinical parameter to detect pulmonary hypertension (PH) in patients. Results on a dataset of 24 patients show that quantitative indices derived from the segmentation are applicable to distinguish patients with and without PH. Further work-in-progress results are shown on the VESSEL12 challenge dataset, which is composed of non-contrast-enhanced scans, where we range in the midfield of participating contestants.
@article{arxiv.1304.7140,
title = {Pulmonary Vascular Tree Segmentation from Contrast-Enhanced CT Images},
author = {M. Helmberger and M. Urschler and M. Pienn and Z. Balint and A. Olschewski and H. Bischof},
journal= {arXiv preprint arXiv:1304.7140},
year = {2013}
}
Comments
Part of the OAGM/AAPR 2013 proceedings (1304.1876)