SU-E-T-409: A Comparison of 3D Optical Surface and IR Marker Tracking for Head Motion Compensated Frameless SRS

2012 ◽  
Vol 39 (6Part16) ◽  
pp. 3798-3798
Author(s):  
R Wiersma ◽  
S Tomarken ◽  
Z Grelewicz ◽  
H Kang
Keyword(s):  
Head Motion ◽  
Optical Surface ◽  
Marker Tracking

Variation of the amount of hydrogen along the galactic ridge

1967 ◽  
Vol 31 ◽  
pp. 171-172
Author(s):  
Th. Schmidt-Kaler
Keyword(s):  
Surface Brightness ◽  
Milky Way ◽  
Neutral Hydrogen ◽  
Line Of Sight ◽  
Optical Surface ◽  
Hydrogen Density ◽  
Continuous Radiation ◽  
Galactic Longitude

The integralNHof neutral-hydrogen density along the line of sight is determined from the Kootwijk and Sydney surveys. The run ofNHwith galactic longitude agrees well with that of thermal continuous radiation and that of the optical surface brightness of the Milky Way.

fMRI Simulator Training to Suppress Head Motion

2016 ◽  
Vol 4 (2) ◽  
pp. 96-103 ◽  
Author(s):  
S. J. Graham ◽  
S. Ranieri ◽  
S. Boe ◽  
J. E. Ween ◽  
F. Tam ◽  
...  
Keyword(s):  
Simulator Training ◽  
Head Motion

Optical Surface Photometry of a Sample of Disk Galaxies. I. Observations and Data Reduction

2000 ◽  
Vol 119 (4) ◽  
pp. 1638-1644 ◽  
Author(s):  
J. A. L. Aguerri ◽  
A. M. Varela ◽  
M. Prieto ◽  
C. Muñoz-Tuñón
Keyword(s):  
Data Reduction ◽  
Disk Galaxies ◽  
Surface Photometry ◽  
Optical Surface

A Critical, Event-Related Appraisal of Denoising in Resting-State fMRI Studies

2020 ◽  
Vol 30 (10) ◽  
pp. 5544-5559 ◽  
Author(s):  
Jonathan D Power ◽  
Charles J Lynch ◽  
Babatunde Adeyemo ◽  
Steven E Petersen
Keyword(s):  
Resting State ◽  
Resting State Fmri ◽  
Critical Event ◽  
Head Motion ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Decay Properties ◽  
Signal Decay ◽  
Biological Variables ◽  
Related Approach

Abstract This article advances two parallel lines of argument about resting-state functional magnetic resonance imaging (fMRI) signals, one empirical and one conceptual. The empirical line creates a four-part organization of the text: (1) head motion and respiration commonly cause distinct, major, unwanted influences (artifacts) in fMRI signals; (2) head motion and respiratory changes are, confoundingly, both related to psychological and clinical and biological variables of interest; (3) many fMRI denoising strategies fail to identify and remove one or the other kind of artifact; and (4) unremoved artifact, due to correlations of artifacts with variables of interest, renders studies susceptible to identifying variance of noninterest as variance of interest. Arising from these empirical observations is a conceptual argument: that an event-related approach to task-free scans, targeting common behaviors during scanning, enables fundamental distinctions among the kinds of signals present in the data, information which is vital to understanding the effects of denoising procedures. This event-related perspective permits statements like “Event X is associated with signals A, B, and C, each with particular spatial, temporal, and signal decay properties”. Denoising approaches can then be tailored, via performance in known events, to permit or suppress certain kinds of signals based on their desirability.

scholarly journals Individual Differences in Impulsivity Predict Head Motion during Magnetic Resonance Imaging

PLoS ONE ◽  
2014 ◽  
Vol 9 (8) ◽  
pp. e104989 ◽  
Author(s):  
Xiang-zhen Kong ◽  
Zonglei Zhen ◽  
Xueting Li ◽  
Huan-hua Lu ◽  
Ruosi Wang ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Individual Differences ◽  
Magnetic Resonance ◽  
Head Motion ◽  
Resonance Imaging

Quantifying the psychopathic stare: Automated assessment of head motion is related to antisocial traits in forensic interviews

2021 ◽  
pp. 104093
Author(s):  
Aparna R. Gullapalli ◽  
Nathaniel E. Anderson ◽  
Rohit Yerramsetty ◽  
Carla L. Harenski ◽  
Kent A. Kiehl
Keyword(s):  
Head Motion ◽  
Automated Assessment ◽  
Forensic Interviews

scholarly journals A unified evaluation framework for head motion prediction methods in 360° videos

2020 ◽  
Author(s):  
Miguel Fabián Romero Rondón ◽  
Lucile Sassatelli ◽  
Ramón Aparicio-Pardo ◽  
Frédéric Precioso
Keyword(s):  
Evaluation Framework ◽  
Motion Prediction ◽  
Head Motion ◽  
Prediction Methods
Sign in / Sign up

Export Citation Format

Share Document