Table of Contents
Journal of Medical Engineering
Volume 2013, Article ID 340821, 8 pages
http://dx.doi.org/10.1155/2013/340821
Research Article

Markerless Lung Tumor Motion Tracking by Dynamic Decomposition of X-Ray Image Intensity

1Tohoku University Graduate School of Medicine, Sendai 980-8575, Japan
2Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, Japan
3St. Luke’s International Hospital, Tokyo 104-8560, Japan
4Graduate School of Engineering, Tohoku University, Sendai 980-8579, Japan
5Center for Information Technology in Education, Tohoku University, Sendai 980-8576, Japan
6Cyberscience Center, Tohoku University, Sendai 980-8578, Japan

Received 12 June 2013; Revised 27 October 2013; Accepted 29 October 2013

Academic Editor: Eugene Fourkal

Copyright © 2013 Noriyasu Homma 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.

Abstract

We propose a new markerless tracking technique of lung tumor motion by using an X-ray fluoroscopic image sequence for real-time image-guided radiation therapy (IGRT). A core innovation of the new technique is to extract a moving tumor intensity component from the fluoroscopic image intensity. The fluoroscopic intensity is the superimposition of intensity components of all the structures passed through by the X-ray. The tumor can then be extracted by decomposing the fluoroscopic intensity into the tumor intensity component and the others. The decomposition problem for more than two structures is ill posed, but it can be transformed into a well-posed one by temporally accumulating constraints that must be satisfied by the decomposed moving tumor component and the rest of the intensity components. The extracted tumor image can then be used to achieve accurate tumor motion tracking without implanted markers that are widely used in the current tracking techniques. The performance evaluation showed that the extraction error was sufficiently small and the extracted tumor tracking achieved a high and sufficient accuracy less than 1 mm for clinical datasets. These results clearly demonstrate the usefulness of the proposed method for markerless tumor motion tracking.