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The Scientific World Journal
Volume 2012, Article ID 913693, 8 pages
Research Article

Deformable Image Registration with Inclusion of Autodetected Homologous Tissue Features

1Key Laboratory for Health Informatics, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
2Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA 94305-5847, USA

Received 31 October 2011; Accepted 11 December 2011

Academic Editor: Constantin Kappas

Copyright © 2012 Qingsong Zhu 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.


A novel deformable registration algorithm is proposed in the application of radiation therapy. The algorithm starts with autodetection of a number of points with distinct tissue features. The feature points are then matched by using the scale invariance features transform (SIFT) method. The associated feature point pairs are served as landmarks for the subsequent thin plate spline (TPS) interpolation. Several registration experiments using both digital phantom and clinical data demonstrate the accuracy and efficiency of the method. For the 3D phantom case, markers with error less than 2 mm are over 85% of total test markers, and it takes only 2-3 minutes for 3D feature points association. The proposed method provides a clinically practical solution and should be valuable for various image-guided radiation therapy (IGRT) applications.