Optimization of non-linear image registration in AFNI
J Yin, T Anthony, J Marstrander, Y Liu…�- Proceedings of the�…, 2016 - dl.acm.org
… aspect of fMRI image analysis [12]. The … image registration program 3dQwarp, and an
improvement in terms of both the parallel efficiency of the code and the fidelity of the warped image…
improvement in terms of both the parallel efficiency of the code and the fidelity of the warped image…
[PDF][PDF] Robust methods for medical image registration with application in clinical diagnosis
AFS Ribeiro - 2017 - core.ac.uk
… The advances of image processing frameworks allow not only a more accurate … circuits,
whilst functional Magnetic Resonance Imaging (fMRI) has been used to understand the intrinsic …
whilst functional Magnetic Resonance Imaging (fMRI) has been used to understand the intrinsic …
Processing, evaluating and understanding FMRI data with afni_proc. py
… available AFNI toolbox (Cox, 1996), to create full processing pipelines across this wide
FMRI … The quality of nonlinear warping results using 3dQwarp (which also underlies @SSwarper, …
FMRI … The quality of nonlinear warping results using 3dQwarp (which also underlies @SSwarper, …
NRAAF: A Framework for Comparative Analysis of fMRI Registration Algorithms and Their Impact on Resting-State Neuroimaging Accuracy
… FNIRT and AFNI’s 3dQwarp differ in their specific approaches to non-linear registration. FSL’…
as well as deep learning-based medical image registration were considered for use in this …
as well as deep learning-based medical image registration were considered for use in this …
Assessing methods for geometric distortion compensation in 7T gradient echo fMRI data
… Mutual information is often used to assess multi-modal brain image registration 54 , and should
… The second (SE 3dQwarp) condition used AFNI’s 3dQwarp as described above to apply …
… The second (SE 3dQwarp) condition used AFNI’s 3dQwarp as described above to apply …
Assessing methods for geometric distortion compensation in 7 T gradient echo functional MRI data
… AFNI's 3dQwarp, both the AP and PA scans were independently masked using AFNI's
3dAutomask to remove nonbrain image … compensation was calculated using 3dQwarp with the -…
3dAutomask to remove nonbrain image … compensation was calculated using 3dQwarp with the -…
[HTML][HTML] Quality control practices in FMRI analysis: Philosophy, methods and examples using AFNI
… For example, image registration is driven by a quantitative cost function, but then separate
assessment is needed to verify that tissue boundaries and sulcal and gyral patterns appear to …
assessment is needed to verify that tissue boundaries and sulcal and gyral patterns appear to …
Distortion correction of functional MRI without reverse phase encoding scans or field maps
… (for example, using FSL's topup or AFNI's 3dQwarp algorithms) require the collection of …
], its ability to act as an image processing intermediate, or a substrate for distortion correction…
], its ability to act as an image processing intermediate, or a substrate for distortion correction…
[HTML][HTML] A Set of FMRI Quality Control Tools in AFNI: Systematic, in-depth and interactive QC with afni_proc. py and more
… throughout any single subject processing pipeline, both quantitatively and qualitatively.
We present several FMRI preprocessing QC features available in the AFNI toolbox, many of …
We present several FMRI preprocessing QC features available in the AFNI toolbox, many of …
FMRI clustering in AFNI: false-positive rates redux
… The detailed AFNI processing for individual subjects was somewhat different than in ENK16…
, AnatICOR for denoising, and 3dQwarp for nonlinear registration; see Supplementary Data (…
, AnatICOR for denoising, and 3dQwarp for nonlinear registration; see Supplementary Data (…