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Mendeley readers
Attention Score in Context
| Title |
lop-DWI: A Novel Scheme for Pre-Processing of Diffusion-Weighted Images in the Gradient Direction Domain
|
|---|---|
| Published in |
Frontiers in Neurology, January 2015
|
| DOI | 10.3389/fneur.2014.00290 |
| Pubmed ID | |
| Authors |
Farshid Sepehrband, Jeiran Choupan, Emmanuel Caruyer, Nyoman D. Kurniawan, Yaniv Gal, Quang M. Tieng, Katie L. McMahon, Viktor Vegh, David C. Reutens, Zhengyi Yang |
| Abstract |
We describe and evaluate a pre-processing method based on a periodic spiral sampling of diffusion-gradient directions for high angular resolution diffusion magnetic resonance imaging. Our pre-processing method incorporates prior knowledge about the acquired diffusion-weighted signal, facilitating noise reduction. Periodic spiral sampling of gradient direction encodings results in an acquired signal in each voxel that is pseudo-periodic with characteristics that allow separation of low-frequency signal from high frequency noise. Consequently, it enhances local reconstruction of the orientation distribution function used to define fiber tracks in the brain. Denoising with periodic spiral sampling was tested using synthetic data and in vivo human brain images. The level of improvement in signal-to-noise ratio and in the accuracy of local reconstruction of fiber tracks was significantly improved using our method. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 13 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 31% |
| Researcher | 3 | 23% |
| Other | 2 | 15% |
| Unknown | 4 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 2 | 15% |
| Engineering | 2 | 15% |
| Medicine and Dentistry | 1 | 8% |
| Computer Science | 1 | 8% |
| Unknown | 7 | 54% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 February 2015.
All research outputs
#15,907,007
of 24,226,848 outputs
Outputs from Frontiers in Neurology
#6,584
of 13,253 outputs
Outputs of similar age
#207,168
of 361,025 outputs
Outputs of similar age from Frontiers in Neurology
#55
of 84 outputs
Altmetric has tracked 24,226,848 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,253 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one is in the 45th percentile – i.e., 45% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 361,025 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 84 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.