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3.0 tesla allegra

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The 3.0 Tesla Allegra is a high-field magnetic resonance imaging (MRI) system designed for research and clinical applications. It provides a magnetic field strength of 3.0 Tesla, which enables high-resolution imaging and advanced imaging techniques.

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Allegra 3.0 Tesla scanner (6 citations) 3.0 Tesla Allegra MRI scanner (3 citations) 3 Tesla Allegra (2 citations) 3.0 Tesla (2 citations)

2 protocols using 3.0 tesla allegra

1

Healthy Resting-State fMRI Neuroimaging Dataset

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Forty healthy participants generously posted in NITRC site for public use were downloaded (http://fcon_1000.projects.nitrc.org/fcpClassic/FcpTable.html). This dataset was generated by the Milham and Castellanos groups (Castellanos et al., 2009 (link)). In the present study, 6 subjects were discarded according to our quality control procedure, including visual inspection of the final images, and automatic rejection by AFNI (afni_proc.py), and 34 subjects (15 males and 19 females ranging from 12.2 to 25.2 years old (mean ± SD: 19.9 ± 4.2)) were kept. Resting state time series (one run per subject) data were acquired using echo planar imaging on a Siemens 3.0 Tesla Allegra (TR = 2000 ms; TE = 25 ms; flip angle = 90, 39 slices, matrix = 64 × 64; FOV = 192mm; acquisition voxel size = 3 × 3 × 3mm; 6.5 min.
Garin C.M., Hori Y., Everling S., Whitlow C.T., Calabro F.J., Luna B., Froesel M., Gacoin M., Hamed S.B., Dhenain M, & Constantinidis C. (2022). An evolutionary gap in primate default mode network organization. Cell reports, 39(2), 110669.
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2

Healthy Resting-State fMRI Neuroimaging Dataset

Check if the same lab product or an alternative is used in the 5 most similar protocols
Forty healthy participants generously posted in NITRC site for public use were downloaded (http://fcon_1000.projects.nitrc.org/fcpClassic/FcpTable.html). This dataset was generated by the Milham and Castellanos groups (Castellanos et al., 2009 (link)). In the present study, 6 subjects were discarded according to our quality control procedure, including visual inspection of the final images, and automatic rejection by AFNI (afni_proc.py), and 34 subjects (15 males and 19 females ranging from 12.2 to 25.2 years old (mean ± SD: 19.9 ± 4.2)) were kept. Resting state time series (one run per subject) data were acquired using echo planar imaging on a Siemens 3.0 Tesla Allegra (TR = 2000 ms; TE = 25 ms; flip angle = 90, 39 slices, matrix = 64 × 64; FOV = 192mm; acquisition voxel size = 3 × 3 × 3mm; 6.5 min.
Garin C.M., Hori Y., Everling S., Whitlow C.T., Calabro F.J., Luna B., Froesel M., Gacoin M., Hamed S.B., Dhenain M, & Constantinidis C. (2022). An evolutionary gap in primate default mode network organization. Cell reports, 39(2), 110669.
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