Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain.
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TLDR
This study indicates that SyN, with cross-correlation, is a reliable method for normalizing and making anatomical measurements in volumetric MRI of patients and at-risk elderly individuals.About:
This article is published in Medical Image Analysis.The article was published on 2008-02-01 and is currently open access. It has received 4233 citations till now. The article focuses on the topics: Large deformation diffeomorphic metric mapping & Population.read more
Citations
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A reproducible evaluation of ANTs similarity metric performance in brain image registration.
TL;DR: This is the first study to use a consistent transformation framework to provide a reproducible evaluation of the isolated effect of the similarity metric on optimal template construction and brain labeling, and to quantify the similarity of templates derived from different subgroups.
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Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration.
Arno Klein,Jesper L. R. Andersson,Babak A. Ardekani,Babak A. Ardekani,John Ashburner,Brian B. Avants,Ming Chang Chiang,Gary E. Christensen,D. Louis Collins,James C. Gee,Pierre Hellier,Pierre Hellier,Joo Hyun Song,Mark Jenkinson,Claude Lepage,Daniel Rueckert,Paul M. Thompson,Tom Vercauteren,Tom Vercauteren,Roger P. Woods,J. John Mann,Ramin V. Parsey +21 more
TL;DR: This study is the largest evaluation of nonlinear deformation algorithms applied to brain image registration ever conducted and suggests that the findings are generalizable to new subject populations that are labeled or evaluated using different labeling protocols.
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Unbiased Average Age-Appropriate Atlases for Pediatric Studies
Vladimir S. Fonov,Alan C. Evans,Kelly N. Botteron,C. Robert Almli,Robert C. McKinstry,D. Louis Collins +5 more
TL;DR: The methods used to create unbiased, age-appropriate MRI atlas templates for pediatric studies that represent the average anatomy for the age range of 4.5-18.5 years are presented, while maintaining a high level of anatomical detail and contrast.
Journal ArticleDOI
fMRIPrep: a robust preprocessing pipeline for functional MRI
Oscar Esteban,Christopher J. Markiewicz,Ross Blair,Craig A. Moodie,Ayse Ilkay Isik,Asier Erramuzpe,James D. Kent,Mathias Goncalves,Elizabeth DuPre,Snyder M,Hiroyuki Oya,Satrajit S. Ghosh,Satrajit S. Ghosh,Jessey Wright,Joke Durnez,Russell A. Poldrack,Krzysztof J. Gorgolewski +16 more
TL;DR: fMRIPrep is a robust and easy-to-use pipeline for preprocessing of diverse fMRI data that dispenses of manual intervention, thereby ensuring the reproducibility of the results.
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Deformable Medical Image Registration: A Survey
TL;DR: This paper attempts to give an overview of deformable registration methods, putting emphasis on the most recent advances in the domain, and provides an extensive account of registration techniques in a systematic manner.
References
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Book
Ordinary differential equations
TL;DR: The fourth volume in a series of volumes devoted to self-contained and up-to-date surveys in the theory of ODEs was published by as discussed by the authors, with an additional effort to achieve readability for mathematicians and scientists from other related fields so that the chapters have been made accessible to a wider audience.
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Nonrigid registration using free-form deformations: application to breast MR images
TL;DR: The results clearly indicate that the proposed nonrigid registration algorithm is much better able to recover the motion and deformation of the breast than rigid or affine registration algorithms.
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Multimodality image registration by maximization of mutual information
TL;DR: The results demonstrate that subvoxel accuracy with respect to the stereotactic reference solution can be achieved completely automatically and without any prior segmentation, feature extraction, or other preprocessing steps which makes this method very well suited for clinical applications.
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Medical image analysis: progress over two decades and the challenges ahead
James S. Duncan,Nicholas Ayache +1 more
TL;DR: A look at progress in the field over the last 20 years is looked at and some of the challenges that remain for the years to come are suggested.