Joint segmentation and groupwise registration of cardiac perfusion images using temporal information

Journal of Digital Imaging
Dwarikanath Mahapatra


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.


Jan 29, 2013·Journal of Digital Imaging·Dwarikanath Mahapatra
Oct 6, 2014·Medical Physics·Garth M BeacheGeorgy Gimel'farb
Jan 10, 2016·Medical Physics·Zhoubo LiCynthia H McCollough
Jun 5, 2014·Journal of Digital Imaging·Dwarikanath Mahapatra
Jan 16, 2013·Journal of Digital Imaging·Dwarikanath Mahapatra


Oct 26, 1999·IEEE Transactions on Medical Imaging·D RueckertD J Hawkes
Feb 10, 2006·NeuroImage·Kilian M PohlWilliam M Wells
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Nov 27, 2007·NeuroImage·David W ShattuckArthur W Toga
Mar 17, 2009·NeuroImage·Songyuan TangDinggang Shen
Nov 26, 2010·IEEE Transactions on Bio-medical Engineering·Dwarikanath Mahapatra, Ying Sun
Jul 28, 2011·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Dwarikanath Mahapatra, Ying Sun

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