Table of Contents
ISRN Machine Vision
Volume 2012 (2012), Article ID 705853, 9 pages
Research Article

Joint Segmentation and Groupwise Registration of Cardiac Perfusion Images Using Temporal Information

Department of Computer Science, Swiss Federal Institute of Technology, 8092 Zurich, Switzerland

Received 31 January 2012; Accepted 5 March 2012

Academic Editors: C.-C. Han, S. Li, and D. P. Mukherjee

Copyright © 2012 Dwarikanath Mahapatra. 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.


We propose a joint segmentation and groupwise registration method for cardiac perfusion images by using temporal information. The nature of perfusion images makes groupwise registration especially attractive as the temporal information from the entire image sequence can be used. Registration aims to maximize the smoothness of the intensity signal, while segmentation minimizes a pixel’s dissimilarity with other pixels having the same segmentation label. The cost function is optimized in an iterative fashion using B-splines. Tests on real patient datasets show that compared to two other methods, our method shows lower registration error and higher segmentation accuracy. This is attributed to the use of temporal information for groupwise registration and mutually complementary registration and segmentation information in one framework, while other methods solve the two problems separately.