A multi-institution evaluation of deformable image registration algorithms for automatic organ delineation in adaptive head and neck radiotherapy

Authors

Nicholas Hardcastle, University of Wisconsin - MadisonFollow
Wolfgang A. Tome, University of WollongongFollow
Donald M. Cannon, University of Wisconsin
Charlotte L. Brouwer, University of Groningen
Paul W. H Wittendorp, University of Groningen
Nesrin Dogan, Virginia-Commonwealth-University
Matthias Guckenberger, University Hospital Wurzburg
Stephane Allaire, Princess Margaret Hospital
Yogish Mallya, Phillips Electrical
Prashant Kumar, Philips Electronics
Markus Oechsner, University Hospital Wurzburg
Anne Richter, University Hospital Wurzburg
Shiyu Song, Virginia Commonwealth University
Michael Myers, Virginia Commonwealth University
Bulent Polat, University Hospital Wurzburg
Karl Bzdusek, Phillips Radial Oncology System

RIS ID

65694

Publication Details

Hardcastle, N., Tome, W. A., Cannon, D. M., Brouwer, C. L., Wittendorp, P. W. H., Dogan, N., Guckenberger, M., Allaire, S., Mallya, Y., Kumar, P., Oechsner, M., Richter, A., Song, S., Myers, M., Polat, B. & Bzdusek, K. (2012). A multi-institution evaluation of deformable image registration algorithms for automatic organ delineation in adaptive head and neck radiotherapy. Radiation Oncology, 7 (1), 90-96.

Abstract

Background: Adaptive Radiotherapy aims to identify anatomical deviations during a radiotherapy course and modify the treatment plan to maintain treatment objectives. This requires regions of interest (ROIs) to be defined using the most recent imaging data. This study investigates the clinical utility of using deformable image registration (DIR) to automatically propagate ROIs.