Joint segmentation and groupwise registration of cardiac perfusion images using temporal information.
We propose a joint segmentation and groupwise registration method for dynamic cardiac perfusion images that uses 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 with 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 mutual complementary registration and segmentation information in one framework while other methods solve the two problems separately.
Department of Computer Science, Swiss Federal Institute of Technology (ETH) Zurich, Room CAB F 61.1, Universitätstrasse 6, 8092, Zurich, Switzerland. dwarikanath.mahapatra@inf.ethz.ch
Dwarikanath
D
Mahapatra
D000465:Algorithms; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D006352:Heart Ventricles / Q000000981:diagnostic imaging; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D021621:Imaging, Three-Dimensional; D008955:Models, Cardiovascular; D009206:Myocardium / Q000473:pathology; D055420:Perfusion Imaging / Q000379:methods; D012680:Sensitivity and Specificity; D013382:Subtraction Technique