Impact of prospective motion correction, distortion correction methods and large vein bias on the spatial accuracy of cortical laminar fMRI at 9.4 Tesla

Preprocessing

10.1093/oso/9780198793816.003.0003 ◽

2017 ◽

Author(s):

Michael Chappell ◽

Bradley MacIntosh ◽

Thomas Okell

Keyword(s):

Arterial Spin Labeling ◽

Motion Correction ◽

Spatial Filtering ◽

Spin Labeling ◽

Distortion Correction

In neuroimaging studies, a number of preprocessing steps are often applied to MRI data to correct for artifacts that arise during acquisition. This chapter discusses the main options for arterial spin labeling (ASL) data, along with some of the specific ways in which these can improve the data, but can also interact with subsequent analysis steps. The chapter focuses on motion correction, distortion correction, registration, and spatial filtering as the main preprocessing options commonly applied to perfusion images.

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Combining prospective motion correction and distortion correction for EPI: towards a comprehensive correction of motion and susceptibility-induced artifacts

Magnetic Resonance Materials in Physics Biology and Medicine ◽

10.1007/s10334-010-0225-8 ◽

2010 ◽

Vol 23 (4) ◽

pp. 263-273 ◽

Cited By ~ 24

Author(s):

Rainer Boegle ◽

Julian Maclaren ◽

Maxim Zaitsev

Keyword(s):

Motion Correction ◽

Distortion Correction

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The developing Human Connectome Project (dHCP) automated resting-state functional processing framework for newborn infants

10.1101/766030 ◽

2019 ◽

Cited By ~ 6

Author(s):

Sean P. Fitzgibbon ◽

Samuel J. Harrison ◽

Mark Jenkinson ◽

Luke Baxter ◽

Emma C. Robinson ◽

...

Keyword(s):

Resting State ◽

Motion Correction ◽

Substantial Reduction ◽

Distortion Correction ◽

Fmri Data ◽

Dynamic Susceptibility ◽

List Type ◽

High Quality ◽

Multimodal Registration ◽

Human Connectome Project

AbstractThe developing Human Connectome Project (dHCP) aims to create a detailed 4-dimensional connectome of early life spanning 20 to 45 weeks post-menstrual age. This is being achieved through the acquisition of multi-modal MRI data from over 1000 in- and ex-utero subjects combined with the development of optimised pre-processing pipelines. In this paper we present an automated and robust pipeline to minimally pre-process highly confounded neonatal resting-state fMRI data, robustly, with low failure rates and high quality-assurance. The pipeline has been designed to specifically address the challenges that neonatal data presents including low and variable contrast and high levels of head motion. We provide a detailed description and evaluation of the pipeline which includes integrated slice-to-volume motion correction and dynamic susceptibility distortion correction, a robust multimodal registration approach, bespoke ICA-based denoising, and an automated QC framework. We assess these components on a large cohort of dHCP subjects and demonstrate that processing refinements integrated into the pipeline provide substantial reduction in movement related distortions, resulting in significant improvements in SNR, and detection of high quality RSNs from neonates.HighlightsAn automated and robust pipeline to minimally pre-process highly confounded neonatal fMRI dataIncludes integrated dynamic distortion and slice-to-volume motion correctionA robust multimodal registration approach which includes custom neonatal templatesIncorporates an automated and self-reporting QC framework to quantify data quality and identify issues for further inspectionData analysis of 538 infants imaged at 26-45 weeks post-menstrual age

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Assessing the performance of different DTI motion correction strategies in the presence of EPI distortion correction

Human Brain Mapping ◽

10.1002/hbm.23318 ◽

2016 ◽

Vol 37 (12) ◽

pp. 4405-4424 ◽

Cited By ~ 19

Author(s):

Paul A. Taylor ◽

A. Alhamud ◽

Andre van der Kouwe ◽

Muhammad G. Saleh ◽

Barbara Laughton ◽

...

Keyword(s):

Motion Correction ◽

Distortion Correction ◽

Correction Strategies

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QSIPrep: An integrative platform for preprocessing and reconstructing diffusion MRI

10.1101/2020.09.04.282269 ◽

2020 ◽

Author(s):

Matthew Cieslak ◽

Philip A. Cook ◽

Xiaosong He ◽

Fang-Cheng Yeh ◽

Thijs Dhollander ◽

...

Keyword(s):

Best Practices ◽

Diffusion Mri ◽

Motion Correction ◽

Distortion Correction ◽

Reproducible Research ◽

Resonance Imaging ◽

Sampling Schemes ◽

File Formats ◽

Weighted Magnetic Resonance Imaging ◽

Software Platforms

ABSTRACTDiffusion-weighted magnetic resonance imaging (dMRI) has become the primary method for non-invasively studying the organization of white matter in the human brain. While many dMRI acquisition sequences have been developed, they all sample q-space in order to characterize water diffusion. Numerous software platforms have been developed for processing dMRI data, but most work on only a subset of sampling schemes or implement only parts of the processing workflow. Reproducible research and comparisons across dMRI methods are hindered by incompatible software, diverse file formats, and inconsistent naming conventions. Here we introduce QSIPrep, an integrative software platform for the processing of diffusion images that is compatible with nearly all dMRI sampling schemes. Drawing upon a diverse set of software suites to capitalize upon their complementary strengths, QSIPrep automatically applies best practices for dMRI preprocessing, including denoising, distortion correction, head motion correction, coregistration, and spatial normalization. Throughout, QSIPrep provides both visual and quantitative measures of data quality as well as “glass-box” methods reporting. Taken together, these features facilitate easy implementation of best practices for processing of diffusion images while simultaneously ensuring reproducibility.

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SPECTRA: A program for processing electron images of crystals

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100121065 ◽

1992 ◽

Vol 50 (1) ◽

pp. 132-133

Author(s):

M.F. Schmid ◽

R. Dargahi ◽

M. W. Tam

Keyword(s):

Lattice Distortion ◽

Data Transfer ◽

Reciprocal Lattice ◽

Data Entry ◽

Image Data ◽

Distortion Correction ◽

Specimen Preparation ◽

Electron Image ◽

Computer Controlled ◽

Program Modules

Electron crystallography is an emerging field for structure determination as evidenced by a number of membrane proteins that have been solved to near-atomic resolution. Advances in specimen preparation and in data acquisition with a 400kV microscope by computer controlled spot scanning mean that our ability to record electron image data will outstrip our capacity to analyze it. The computed fourier transform of these images must be processed in order to provide a direct measurement of amplitudes and phases needed for 3-D reconstruction.In anticipation of this processing bottleneck, we have written a program that incorporates a menu-and mouse-driven procedure for auto-indexing and refining the reciprocal lattice parameters in the computed transform from an image of a crystal. It is linked to subsequent steps of image processing by a system of data bases and spawned child processes; data transfer between different program modules no longer requires manual data entry. The progress of the reciprocal lattice refinement is monitored visually and quantitatively. If desired, the processing is carried through the lattice distortion correction (unbending) steps automatically.

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Motion correction eliminates discontinuities in parametric PET images of neuroreceptor binding

Journal of Cerebral Blood Flow & Metabolism ◽

10.1038/sj.jcbfm.9591524.0622 ◽

2005 ◽

Vol 25 (1_suppl) ◽

pp. S622-S622

Author(s):

Hans R Herzog ◽

Lutz Tellmann ◽

Roger Fulton ◽

Isabelle Stangier ◽

Elena Rota Kops ◽

...

Keyword(s):

Motion Correction

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Motion correction in PET/CT

Nuklearmedizin ◽

10.1055/s-0038-1625215 ◽

2005 ◽

Vol 44 (S 01) ◽

pp. S46-S50 ◽

Cited By ~ 5

Author(s):

M. Dawood ◽

N. Lang ◽

F. Büther ◽

M. Schäfers ◽

O. Schober ◽

...

Keyword(s):

Optical Flow ◽

Motion Correction ◽

Motion Vector ◽

Emission Tomography ◽

Cardiac Pet ◽

Novel Approach ◽

Positron Emission ◽

Pet Ct ◽

Flow Algorithm ◽

Motion Vector Field

Summary:Motion in PET/CT leads to artifacts in the reconstructed PET images due to the different acquisition times of positron emission tomography and computed tomography. The effect of motion on cardiac PET/CT images is evaluated in this study and a novel approach for motion correction based on optical flow methods is outlined. The Lukas-Kanade optical flow algorithm is used to calculate the motion vector field on both simulated phantom data as well as measured human PET data. The motion of the myocardium is corrected by non-linear registration techniques and results are compared to uncorrected images.

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