Automatic segmentation of intra-treatment CT images for adaptive radiation therapy of the prostate

Authors:
B. C. Davis;M. Foskey;J. Rosenman;L. Goyal;S. Chang;S. Joshi
Affiliations:
Department of Computer Science, University of North Carolina;Department of Computer Science, University of North Carolina;Department of Radiation Oncology, University of North Carolina;Department of Radiation Oncology, University of North Carolina;Department of Radiation Oncology, University of North Carolina;Department of Computer Science, University of North Carolina
Venue:
MICCAI'05 Proceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Year:
2005

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Abstract

We have been developing an approach for automatically quantifying organ motion for adaptive radiation therapy of the prostate. Our approach is based on deformable image registration, which makes it possible to establish a correspondence between points in images taken on different days. This correspondence can be used to study organ motion and to accumulate inter-fraction dose. In prostate images, however, the presence of bowel gas can cause significant correspondence errors. To account for this problem, we have developed a novel method that combines large deformation image registration with a bowel gas segmentation and deflation algorithm. In this paper, we describe our approach and present a study of its accuracy for adaptive radiation therapy of the prostate. All experiments are carried out on 3-dimensional CT images.