scholarly journals Controlling motion artefact levels in MR images by suspending data acquisition during periods of head motion

2017 ◽  
Author(s):  
Rémi Castella ◽  
Lionel Arn ◽  
Estelle Dupuis ◽  
Martina F. Callaghan ◽  
Bogdan Draganski ◽  
...  
Keyword(s):  
Data Quality ◽  
Data Acquisition ◽  
Motion Correction ◽  
Head Movements ◽  
Head Motion ◽  
Motion Artefacts ◽  
Motion Artefact ◽  
Position Information ◽  
Trade Off ◽  
Scan Time

AbstractHead movements are a major source of MRI artefacts that hamper radiological assessment and computer-based morphological and functional measures of the human brain. Prospective motion correction techniques continuously update the MRI scanner based on head position information provided by an external tracking system. While prospective motion correction significantly improves data quality, strong motion artefacts may remain with large head motions or when motion takes place at sensitive times of the acquisition. Here we present a framework that allows the suspension of data acquisition when head motion is predicted to have a strong negative impact on data quality. The predictor, calculated in real-time during the acquisition, accounts for the amplitude of the signal acquired at the time of the motion, thereby offering a re-acquisition strategy more efficient than relying on head speed alone. The suspension of data acquisition is governed by the trade-off between image degradation due to motion and prolonging the scan time. This trade-off can be tuned by the user according to the desired level of image quality and the participant‘s tolerability. We test the framework using two motion experiments and two head coils. Significant improvements in data quality are obtained with stringent threshold values for the suspension of acquisition. Substantial reductions in motion artefact levels are also achieved with minimal prolongation of scan time. However, high levels of motion artefacts occasionally remain despite stringent thresholds with the 64-channel head coil, an effect that might be attributed to head movement in the sharp sensitivity profile of this coil.

scholarly journals Head motion during fMRI tasks is reduced in children and adults if participants take breaks

2019 ◽  
Author(s):  
Tobias W. Meissner ◽  
Jon Walbrin ◽  
Marisa Nordt ◽  
Kami Koldewyn ◽  
Sarah Weigelt
Keyword(s):  
Data Acquisition ◽  
Time Lag ◽  
Task Engagement ◽  
Fmri Data ◽  
Head Motion ◽  
List Type ◽  
Positive Effects ◽  
Scan Time ◽  
Pediatric Neuroimaging ◽  
Child Friendly

AbstractHead motion remains a challenging confound in functional magnetic resonance imaging (fMRI) studies of both children and adults. Most pediatric neuroimaging labs have developed experience-based, child-friendly standards concerning e.g. the maximum length of a session or the time between mock scanner training and actual scanning. However, it is unclear which factors of child-friendly neuroimaging approaches are effective in reducing head motion. Here, we investigate three main factors including (i) time lag of mock scanner training to the actual scan, (ii) prior scan time, and (iii) task engagement in a dataset of 77 children (aged 6-13) and 64 adults (aged 18-35) using a multilevel modeling approach. In children, distributing fMRI data acquisition across multiple same-day sessions reduces head motion. In adults, motion is reduced after inside-scanner breaks. Despite these positive effects of splitting up data acquisition, motion increases over the course of a study as well as over the course of a run in both children and adults. Our results suggest that splitting up fMRI data acquisition is an effective tool to reduce head motion in general. At the same time, different ways of splitting up data acquisition benefit children and adults.HighlightsIn children, fMRI data acquisition split into multiple sessions reduces head motionIn adults, fMRI data acquisition split by inside-scanner breaks reduces head motionIn both children and adults, motion increases over the duration of a studyIn both children and adults, motion increases over the duration of a run

scholarly journals Controlling motion artefact levels in MR images by suspending data acquisition during periods of head motion

2018 ◽  
Vol 80 (6) ◽  
pp. 2415-2426 ◽  
Author(s):  
Rémi Castella ◽  
Lionel Arn ◽  
Estelle Dupuis ◽  
Martina F. Callaghan ◽  
Bogdan Draganski ◽  
...  
Keyword(s):  
Data Acquisition ◽  
Head Motion ◽  
Mr Images ◽  
Motion Artefact

Minimizing table time in patients with claustrophobia using focused ferumoxytol-enhanced MR angiography (f-FEMRA): a feasibility study

2021 ◽  
Vol 94 (1125) ◽  
pp. 20210430
Author(s):  
Puja Shahrouki ◽  
Kim-Lien Nguyen ◽  
John M. Moriarty ◽  
Adam N. Plotnik ◽  
Takegawa Yoshida ◽  
...  
Keyword(s):  
Image Quality ◽  
Mr Angiography ◽  
Signal To Noise Ratio ◽  
Diagnostic Image Quality ◽  
Diagnostic Confidence ◽  
Motion Artefact ◽  
Scan Time ◽  
Wilcoxon Rank Sum Test ◽  
Significant Difference ◽  
Noise Ratio

Objectives: To assess the feasibility of a rapid, focused ferumoxytol-enhanced MR angiography (f-FEMRA) protocol in patients with claustrophobia. Methods: In this retrospective study, 13 patients with claustrophobia expressed reluctance to undergo conventional MR angiography, but agreed to a trial of up to 10 min in the scanner bore and underwent f-FEMRA. Thirteen matched control patients who underwent gadolinium-enhanced MR angiography (GEMRA) were identified for comparison of diagnostic image quality. For f-FEMRA, the time from localizer image acquisition to completion of the angiographic acquisition was measured. Two radiologists independently scored images on both f-FEMRA and GEMRA for arterial and venous image quality, motion artefact and diagnostic confidence using a 5-point scale, five being best. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in the aorta and IVC were measured. The Wilcoxon rank-sum test, one-way ANOVA with Tukey correction and two-tailed t tests were utilized for statistical analyses. Results: All scans were diagnostic and assessed with high confidence (scores ≥ 4). Average scan time for f-FEMRA was 6.27 min (range 3.56 to 10.12 min), with no significant difference between f-FEMRA and GEMRA in diagnostic confidence (4.86 ± 0.24 vs 4.69 ± 0.25, p = 0.13), arterial image quality (4.62 ± 0.57 vs 4.65 ± 0.49, p = 0.78) and motion artefact score (4.58 ± 0.49 vs 4.58 ± 0.28, p > 0.99). f-FEMRA scored significantly better for venous image quality than GEMRA (4.62 ± 0.42 vs 4.19 ± 0.56, p = 0.04). CNR in the IVC was significantly higher for steady-state f-FEMRA than GEMRA regardless of the enhancement phase (p < 0.05). Conclusions: Comprehensive vascular MR imaging of the thorax, abdomen and pelvis can be completed in as little as 5 min within the magnet bore using f-FEMRA, facilitating acceptance by patients with claustrophobia and streamlining workflow. Advances in knowledge: A focused approach to vascular imaging with ferumoxytol can be performed in patients with claustrophobia, limiting time in the magnet bore to 10 min or less, while acquiring fully diagnostic images of the thorax, abdomen and pelvis.

Active head movements facilitate compensation for effects of prism displacement on dynamic gait12

2006 ◽  
Vol 16 (1-2) ◽  
pp. 29-33
Author(s):  
Kim R. Gottshall ◽  
Michael E. Hoffer ◽  
Helen S. Cohen ◽  
Robert J. Moore
Keyword(s):  
Head Movement ◽  
Sensory Modality ◽  
Normal Subjects ◽  
The Body ◽  
Head Movements ◽  
Head Motion ◽  
Control Group ◽  
Entire Body ◽  
Group 3 ◽  
Group 2

Study design: Four groups, between-subjects study. Objectives: To investigate the effects of exercise on adaptation of normal subjects who had been artificially spatially disoriented. Background: Many patients referred for rehabilitation experience sensory changes, due to age or disease processes, and these changes affect motor skill. The best way to train patients to adapt to these changes and to improve their sensorimotor skills is unclear. Using normal subjects, we tested the hypothesis that active, planned head movement is needed to adapt to modified visual input. Methods and measures: Eighty male and female subjects who had normal balance on computerized dynamic posturography (CDP) and the dynamic gait index (DGI), were randomly assigned to four groups. All groups donned diagonally shift lenses and were again assessed with CDP and DGI. The four groups were then treated for 20 min. Group 1 (control group) viewed a video, Group 2 performed exercise that involved translating the entire body through space, but without separate, volitional head movement, Group 3 performed exercises which all incorporated volitional, planned head rotations, and Group 4 performed exercises that involved translating the body (as in Group 2) and incorporated volitional, planned head motion (as in Group 3). All subjects were post-tested with CDP and DGI, lenses were removed, and subjects were retested again with CDP and DGI. Results: The groups did not differ significantly on CDP scores but Groups 3 and 4 had significantly better DGI scores than Groups 1 and 2. Conclusions: Active head movement that is specifically planned as part of the exercise is more effective than passive attention or head movements that are not consciously planned, for adapting to sensorimotor change when it incorporates active use of the changed sensory modality, in this case head motion.

scholarly journals The efficacy of different preprocessing steps in reducing motion-related confounds in diffusion MRI connectomics

2020 ◽  
Author(s):  
Stuart Oldham ◽  
Aurina Arnatkevic̆iūtė ◽  
Robert E. Smith ◽  
Jeggan Tiego ◽  
Mark A. Bellgrove ◽  
...  
Keyword(s):  
Diffusion Mri ◽  
Motion Correction ◽  
Healthy Adult ◽  
Structural Connectivity ◽  
Head Motion ◽  
List Type ◽  
Edge Weighting ◽  
Quantitative Metrics ◽  
The Impact ◽  
Connectivity Strength

AbstractHead motion is a major confounding factor in neuroimaging studies. While numerous studies have investigated how motion impacts estimates of functional connectivity, the effects of motion on structural connectivity measured using diffusion MRI have not received the same level of attention, despite the fact that, like functional MRI, diffusion MRI relies on elaborate preprocessing pipelines that require multiple choices at each step. Here, we report a comprehensive analysis of how these choices influence motion-related contamination of structural connectivity estimates. Using a healthy adult sample (N = 252), we evaluated 240 different preprocessing pipelines, devised using plausible combinations of different choices related to explicit head motion correction, tractography propagation algorithms, track seeding methods, track termination constraints, quantitative metrics derived for each connectome edge, and parcellations. We found that an approach to motion correction that includes outlier replacement and within-slice volume correction led to a dramatic reduction in cross-subject correlations between head motion and structural connectivity strength, and that motion contamination is more severe when quantifying connectivity strength using mean tract fractional anisotropy rather than streamline count. We also show that the choice of preprocessing strategy can significantly influence subsequent inferences about network organization, with the location of network hubs varying considerably depending on the specific preprocessing steps applied. Our findings indicate that the impact of motion on structural connectivity can be successfully mitigated using recent motion-correction algorithms that include outlier replacement and within-slice motion correction.HighlightsWe assess how motion affects structural connectivity in 240 preprocessing pipelinesMotion contamination of structural connectivity depends on preprocessing choicesAdvanced motion correction tools reduce motion confoundsFA edge weighting is more susceptible to motion effects than streamline count

scholarly journals Voice-awareness control for a humanoid robot consistent with its body posture and movements

2010 ◽  
Vol 1 (1) ◽  
Author(s):  
Takuma Otsuka ◽  
Kazuhiro Nakadai ◽  
Toru Takahashi ◽  
Kazunori Komatani ◽  
Tetsuya Ogata ◽  
...  
Keyword(s):  
Dynamic Change ◽  
Voice Quality ◽  
Head Movements ◽  
Body Motion ◽  
Spectral Envelope ◽  
Balance Model ◽  
Head Motion ◽  
Axis Rotation ◽  
The Voice ◽  
Horizontal Head

AbstractThis paper presents voice-awareness control consistent with robot’s head movements. For a natural spoken communication between robots and humans, robots must behave and speak the way humans expect them to. The consistency between the robot’s voice quality and its body motion is one of the most especially striking factors in naturalness of robot speech. Our control is based on a new model of spectral envelope modification for vertical head motion, and left-right balance modulation for horizontal head motion. We assume that a pitch-axis rotation, or a vertical head motion, and a yaw-axis rotation, or a horizontal head motion, effect the voice quality independently. The spectral envelope modification model is constructed based on the analysis of human vocalizations. The left-right balance model is established by measuring impulse responses using a pair of microphones. Experimental results show that the voice-awareness is perceivable in a robot-to-robot dialogue when the robots stand up to 150 cm away. The dynamic change in the voice quality is also confirmed in the experiment.

Perceived Depth from Dot Density Change by Lateral Head Movements

Perception ◽  
1996 ◽  
Vol 25 (1_suppl) ◽  
pp. 133-133 ◽  
Author(s):  
K Sakurai ◽  
H Ono
Keyword(s):  
Sine Wave ◽  
Visual Input ◽  
Head Movements ◽  
Trade Off ◽  
Rocking Motion ◽  
Dot Density ◽  
Wave Surfaces ◽  
Perceived Motion ◽  
Random Dot Pattern ◽  
Lateral Head

We investigated whether there is a trade-off between magnitude of perceived depth and that of perceived motion, using density changes (expansion/contraction) in a random-dot pattern yoked to lateral head movements. We simulated sine-wave surfaces with a depth of 0, 1, 2, 4, 8, and 16 cm. Subjects viewed the patterns monocularly while moving their heads from side to side laterally, and reported the magnitude of perceived depth and that of perceived motion. When simulated depth was less than 4 cm, the surfaces looked stationary and the amount of perceived depth was the same as that of simulated depth. When it was more than 4 cm, the surfaces appeared to move in a rocking motion and the amount of perceived depth was smaller than that of simulated depth. The trade-off implies a mechanism which transduces single visual input into depth or motion.

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