Literature DB >> 28603787

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

Yangming Ou1, Dong Hye Ye1, Kilian M Pohl1, Christos Davatzikos1.   

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].

Entities:  

Keywords:  Cardiac MRI; Evaluation; Image Registration; Validation

Year:  2012        PMID: 28603787      PMCID: PMC5462118          DOI: 10.1007/978-3-642-31340-0_22

Source DB:  PubMed          Journal:  Biomed Image Regist Proc


  19 in total

1.  Nonrigid registration using free-form deformations: application to breast MR images.

Authors:  D Rueckert; L I Sonoda; C Hayes; D L Hill; M O Leach; D J Hawkes
Journal:  IEEE Trans Med Imaging       Date:  1999-08       Impact factor: 10.048

2.  A global optimisation method for robust affine registration of brain images.

Authors:  M Jenkinson; S Smith
Journal:  Med Image Anal       Date:  2001-06       Impact factor: 8.545

Review 3.  A review of cardiac image registration methods.

Authors:  Timo Mäkelä; Patrick Clarysse; Outi Sipilä; Nicoleta Pauna; Quoc Cuong Pham; Toivo Katila; Isabelle E Magnin
Journal:  IEEE Trans Med Imaging       Date:  2002-09       Impact factor: 10.048

4.  Construction of a statistical model for cardiac motion analysis using nonrigid image registration.

Authors:  Raghavendra Chandrashekara; Anil Rao; Gerardo Ivar Sanchez-Ortiz; Raad H Mohiaddin; Daniel Rueckert
Journal:  Inf Process Med Imaging       Date:  2003-07

5.  Quantitative comparison of algorithms for inter-subject registration of 3D volumetric brain MRI scans.

Authors:  Babak A Ardekani; Stephen Guckemus; Alvin Bachman; Matthew J Hoptman; Michelle Wojtaszek; Jay Nierenberg
Journal:  J Neurosci Methods       Date:  2005-03-15       Impact factor: 2.390

6.  Spatio-temporal free-form registration of cardiac MR image sequences.

Authors:  Dimitrios Perperidis; Raad H Mohiaddin; Daniel Rueckert
Journal:  Med Image Anal       Date:  2005-10       Impact factor: 8.545

7.  Diffeomorphic demons: efficient non-parametric image registration.

Authors:  Tom Vercauteren; Xavier Pennec; Aymeric Perchant; Nicholas Ayache
Journal:  Neuroimage       Date:  2008-11-07       Impact factor: 6.556

8.  Dense image registration through MRFs and efficient linear programming.

Authors:  Ben Glocker; Nikos Komodakis; Georgios Tziritas; Nassir Navab; Nikos Paragios
Journal:  Med Image Anal       Date:  2008-04-07       Impact factor: 8.545

9.  Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain.

Authors:  B B Avants; C L Epstein; M Grossman; J C Gee
Journal:  Med Image Anal       Date:  2007-06-23       Impact factor: 8.545

10.  Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration.

Authors:  Arno Klein; Jesper Andersson; Babak A Ardekani; John Ashburner; Brian Avants; Ming-Chang Chiang; Gary E Christensen; D Louis Collins; James Gee; Pierre Hellier; Joo Hyun Song; Mark Jenkinson; Claude Lepage; Daniel Rueckert; Paul Thompson; Tom Vercauteren; Roger P Woods; J John Mann; Ramin V Parsey
Journal:  Neuroimage       Date:  2009-01-13       Impact factor: 6.556

View more
  2 in total

1.  Learning Multiparametric Biomarkers for Assessing MR-Guided Focused Ultrasound Treatment of Malignant Tumors.

Authors:  Blake E Zimmerman; Sara Johnson; Henrik Odeen; Jill Shea; Markus D Foote; Nicole Winkler; Sarang C Joshi; Allison Payne
Journal:  IEEE Trans Biomed Eng       Date:  2021-04-21       Impact factor: 4.538

2.  Deformable registration for quantifying longitudinal tumor changes during neoadjuvant chemotherapy.

Authors:  Yangming Ou; Susan P Weinstein; Emily F Conant; Sarah Englander; Xiao Da; Bilwaj Gaonkar; Meng-Kang Hsieh; Mark Rosen; Angela DeMichele; Christos Davatzikos; Despina Kontos
Journal:  Magn Reson Med       Date:  2014-07-15       Impact factor: 4.668

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.