Reliability in multi-site structural MRI studies: Effects of gradient non-linearity correction on phantom and human data

By Jorge Jovicich, S. Czanner, Douglas N. Greve, E. Haley, A. V. D. van der Kouwe, Randy L. Gollub, Daniel P. Kennedy, F. Schmitt, Gregory G. Brown, J. MacFall and 2 more. NeuroImage, 2006

1,347 citations recorded by the source corpus.

Subfields: Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/da6a2ab567a42381c0a114baff41940820114277

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

The Minimal Preprocessing Pipelines for the Human Connectome Project (2013, positive): “The gradient nonlinearity correction warpfield is then calculated for the diffusion data to remove this spatial distortion (Jovicich et al., 2006), and the mean b0 image is distortion corrected.”
Harmonization of cortical thickness measurements across scanners and sites (2017, background): “, 2014), and structural, functional, and diffusion images in general (Jovicich et al., 2006; Takao et al., 2011).”
Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker (2016, result): “This agrees broadly with previous studies investigating the reliability of T1-MRI measures in multi-centre settings (Jovicich et al., 2006; Schnack et al., 2004).”
The Alzheimer's disease neuroimaging initiative (ADNI): MRI methods (2008, neutral): “, 3D gradwarp (19,20); corrections for intensity nonuniformity due to nonuniform receiver coil sensitivity (21); and correction of image intensity nonuniformity due to other causes such as wave effects at 3 T.”
Image processing and analysis methods for the Adolescent Brain Cognitive Development Study (2018, methodology): “Images are next corrected for distortions due to gradient nonlinearities (Jovicich et al., 2006).”
One year brain atrophy evident in healthy aging (2009, methodology): “Briefly, these data were reviewed for quality, automatically corrected for spatial distortion due to gradient nonlinearity (Jovicich et al., 2006) and B1 field inhomogeneity (Sled et al., 1998), registered, and averaged to improve signal-to-noise ratio.”
Tensor-Based Morphometry as a Neuroimaging Biomarker for Alzheimer’s Disease: An MRI Study of 676 AD, MCI, and Normal Subjects (2008, neutral): “level of ventricular expansion is about 10–15% for MCI and greater than 20% for the AD gro (Jovicich et al., 2006), (2) a “B1-correction”, to adjust for image intensity inhomogeneity due to B1 non-uniformity using calibration scans (Jack et al.”
Quantitative multi-parameter mapping of R1, PD*, MT, and R2* at 3T: a multi-center validation (2013, background): “They may be addressed by post-processing if necessary (Jovicich et al., 2006).”
Detection of cortical thickness correlates of cognitive performance: Reliability across MRI scan sessions, scanners, and field strengths (2008, background): “, 2007), it is surprising that there has been fairly little study of the influence of MRI instrument-related factors on the reliability of such putative imaging biomarkers (Han et al., 2006; Jovicich et al., 2006).”
Automatic classification of patients with Alzheimer's disease from structural MRI: A comparison of ten methods using the ADNI database (2011, methodology): “The image geometry correction was the 3D gradwarp correction (Hajnal et al., 2001; Jovicich et al. 2006).”
Effects of memory training on cortical thickness in the elderly (2010, methodology): “All scans were manually reviewed for quality, and automatically corrected for spatial distortion due to gradient nonlinearity (Jovicich et al., 2006) and B1 field inhomogeneity (Sled et al.”
MRI-derived measurements of human subcortical, ventricular and intracranial brain volumes: Reliability effects of scan sessions, acquisition sequences, data analyses, scanner upgrade, scanner vendors and field strengths (2009, neutral): “…as hydration status (Walters et al., 2001), instrument-related factors, such as field strength, scanner manufacturer, imaging magnetic gradients (Jovicich et al., 2006), pulse sequence, and data processing-related factors, including not only software package and version but also the parameters…”