Validation of DRAMMS among 12 Popular Methods in Cross-Subject Cardiac MRI Registration

  • Yangming Ou
  • Dong Hye Ye
  • Kilian M. Pohl
  • Christos Davatzikos
Conference paper

DOI: 10.1007/978-3-642-31340-0_22

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7359)
Cite this paper as:
Ou Y., Ye D.H., Pohl K.M., Davatzikos C. (2012) Validation of DRAMMS among 12 Popular Methods in Cross-Subject Cardiac MRI Registration. In: Dawant B.M., Christensen G.E., Fitzpatrick J.M., Rueckert D. (eds) Biomedical Image Registration. WBIR 2012. Lecture Notes in Computer Science, vol 7359. Springer, Berlin, Heidelberg

Abstract

Cross-subject image registration is the building block for many cardiac studies. In the literature, it is often handled by voxel-wise registration methods. However, studies are lacking to show which methods are more accurate and stable in this context. Aiming at answering this question, this paper evaluates 12 popular registration methods and validates a recently developed method DRAMMS [16] in the context of cross-subject cardiac registration. Our dataset consists of short-axis end-diastole cardiac MR images from 24 subjects, in which non-cardiac structures are removed. Each registration method was applied to all 552 image pairs. Registration accuracy is approximated by Jaccard overlap between deformed expert annotation of source image and the corresponding expert annotation of target image. This accuracy surrogate is further correlated with deformation aggressiveness, which is reflected by minimum, maximum and range of Jacobian determinants. Our study shows that DRAMMS [16] scores high in accuracy and well balances accuracy and aggressiveness in this dataset, followed by ANTs [13], MI-FFD [14], Demons [15], and ART [12]. Our findings in cross-subject cardiac registrations echo those findings in brain image registrations [7].

Keywords

Image Registration Validation Evaluation Cardiac MRI 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Yangming Ou
    • 1
  • Dong Hye Ye
    • 1
  • Kilian M. Pohl
    • 1
  • Christos Davatzikos
    • 1
  1. 1.Section of Biomedical Image Analysis (SBIA), Department of RadiologyUniversity of PennsylvaniaUSA

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