In this paper, we present a computer-aided follow-up (CAF) scheme to support physicians to track interval changes of pulmonary nodules on three dimensional (3D) CT images and to decide the treatment strategies without making any under or over treatment. Our scheme involves analyzing CT histograms to evaluate the volumetric distribution of CT values within pulmonary nodules. A variational Bayesian mixture modeling framework translates the image-derived features into an image-based risk score for predicting the patient recurrence-free survival. Through applying our scheme to follow-up 3D CT images of pulmonary nodules, we demonstrate the potential usefulness of the CAF scheme which can provide the trajectories that can characterize time interval changes of pulmonary nodules.

Date Published: 18 March 2013
PDF: 6 pages
Proc. SPIE 8670, Medical Imaging 2013: Computer-Aided Diagnosis, 86700J (18 March 2013); doi: 10.1117/12.2008113

Published in SPIE Proceedings Vol. 8670:
Medical Imaging 2013: Computer-Aided Diagnosis
Carol L. Novak; Stephen Aylward, Editor(s)