Table of Contents Author Guidelines Submit a Manuscript
International Journal of Biomedical Imaging
Volume 2007 (2007), Article ID 61523, 10 pages
Research Article

ESTERR-PRO: A Setup Verification Software System Using Electronic Portal Imaging

Institute of Communication and Computer Systems, National Technical University of Athens, 9 Iroon Polytechniou Street, Zografos, Athens 15780, Greece

Received 26 January 2006; Revised 5 July 2006; Accepted 18 July 2006

Academic Editor: Haim Azhari

Copyright © 2007 Pantelis A. Asvestas et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The purpose of the paper is to present and evaluate the performance of a new software-based registration system for patient setup verification, during radiotherapy, using electronic portal images. The estimation of setup errors, using the proposed system, can be accomplished by means of two alternate registration methods. (a) The portal image of the current fraction of the treatment is registered directly with the reference image (digitally reconstructed radiograph (DRR) or simulator image) using a modified manual technique. (b) The portal image of the current fraction of the treatment is registered with the portal image of the first fraction of the treatment (reference portal image) by applying a nearly automated technique based on self-organizing maps, whereas the reference portal has already been registered with a DRR or a simulator image. The proposed system was tested on phantom data and on data from six patients. The root mean square error (RMSE) of the setup estimates was 0.8±0.3 (mean value ± standard deviation) for the phantom data and 0.3±0.3 for the patient data, respectively, by applying the two methodologies. Furthermore, statistical analysis by means of the Wilcoxon nonparametric signed test showed that the results that were obtained by the two methods did not differ significantly (P value >0.05).