Literature DB >> 18269991

Validation of non-rigid registration between functional and anatomical magnetic resonance brain images.

Ali Gholipour, Nasser Kehtarnavaz, Richard W Briggs, Kaundinya S Gopinath, Wendy Ringe, Anthony Whittemore, Sergey Cheshkov, Khamid Bakhadirov.   

Abstract

This paper presents a set of validation procedures for nonrigid registration of functional EPI to anatomical MRI brain images. Although various registration techniques have been developed and validated for high-resolution anatomical MRI images, due to a lack of quantitative and qualitative validation procedures, the use of nonrigid registration between functional EPI and anatomical MRI images has not yet been deployed in neuroimaging studies. In this paper, the performance of a robust formulation of a nonrigid registration technique is evaluated in a quantitative manner based on simulated data and is further evaluated in a quantitative and qualitative manner based on in vivo data as compared to the commonly used rigid and affine registration techniques in the neuroimaging software packages. The nonrigid registration technique is formulated as a second-order constrained optimization problem using a free-form deformation model and mutual information similarity measure. Bound constraints, resolution level and cross-validation issues have been discussed to show the degree of accuracy and effectiveness of the nonrigid registration technique. The analyses performed reveal that the nonrigid approach provides a more accurate registration, in particular when the functional regions of interest lie in regions distorted by susceptibility artifacts.

Mesh:

Year:  2008        PMID: 18269991     DOI: 10.1109/TBME.2007.912641

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  5 in total

1.  Optimal setting of image bounding box can improve registration accuracy of diffusion tensor tractography.

Authors:  Masanori Yoshino; Taichi Kin; Toki Saito; Daichi Nakagawa; Hirofumi Nakatomi; Akira Kunimatsu; Hiroshi Oyama; Nobuhito Saito
Journal:  Int J Comput Assist Radiol Surg       Date:  2013-08-20       Impact factor: 2.924

2.  Peeking into the Black Box of Coregistration in Clinical fMRI: Which Registration Methods Are Used and How Well Do They Perform?

Authors:  F D Raslau; L Y Lin; A H Andersen; D K Powell; C D Smith; E J Escott
Journal:  AJNR Am J Neuroradiol       Date:  2018-10-25       Impact factor: 3.825

3.  Individual Variability in Brain Activity: A Nuisance or an Opportunity?

Authors:  John Darrell Van Horn; Scott T Grafton; Michael B Miller
Journal:  Brain Imaging Behav       Date:  2008-12-01       Impact factor: 3.978

4.  Evaluating Similarity Measures for Brain Image Registration.

Authors:  Q R Razlighi; N Kehtarnavaz; S Yousefi
Journal:  J Vis Commun Image Represent       Date:  2013-10       Impact factor: 2.678

5.  Automatic cortical surface reconstruction of high-resolution T1 echo planar imaging data.

Authors:  Ville Renvall; Thomas Witzel; Lawrence L Wald; Jonathan R Polimeni
Journal:  Neuroimage       Date:  2016-04-11       Impact factor: 6.556

  5 in total

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