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

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Abstract

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.

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Acknowledgment

The author would like to thank Dr. Ying Sun of National University of Singapore for providing the cardiac datasets.

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Authors and Affiliations

  1. Department of Computer Science, Swiss Federal Institute of Technology (ETH) Zurich, Room CAB F 61.1, Universitätstrasse 6, 8092, Zurich, Switzerland

    Dwarikanath Mahapatra

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  1. Dwarikanath Mahapatra
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Correspondence to Dwarikanath Mahapatra.

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Mahapatra, D. Joint Segmentation and Groupwise Registration of Cardiac Perfusion Images Using Temporal Information. J Digit Imaging 26, 173–182 (2013). https://doi.org/10.1007/s10278-012-9497-z

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  • DOI: https://doi.org/10.1007/s10278-012-9497-z

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