| Title |
Artifact-free fat-water separation in Dixon MRI using deep learning
|
|---|---|
| Published in |
Journal of Big Data, January 2023
|
| DOI | 10.1186/s40537-022-00677-1 |
| Pubmed ID | |
| Authors |
Nicolas Basty, Marjola Thanaj, Madeleine Cule, Elena P. Sorokin, Yi Liu, E. Louise Thomas, Jimmy D. Bell, Brandon Whitcher |
X Demographics
The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 4 | 33% |
| United States | 1 | 8% |
| Italy | 1 | 8% |
| Japan | 1 | 8% |
| Unknown | 5 | 42% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 10 | 83% |
| Scientists | 2 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 14 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 2 | 14% |
| Professor | 2 | 14% |
| Other | 1 | 7% |
| Lecturer > Senior Lecturer | 1 | 7% |
| Librarian | 1 | 7% |
| Other | 1 | 7% |
| Unknown | 6 | 43% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 2 | 14% |
| Mathematics | 1 | 7% |
| Biochemistry, Genetics and Molecular Biology | 1 | 7% |
| Agricultural and Biological Sciences | 1 | 7% |
| Medicine and Dentistry | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 8 | 57% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 09 February 2023.
All research outputs
#3,083,451
of 25,392,582 outputs
Outputs from Journal of Big Data
#62
of 391 outputs
Outputs of similar age
#62,618
of 475,229 outputs
Outputs of similar age from Journal of Big Data
#1
of 13 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 391 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.6. This one has done well, scoring higher than 84% of its peers.
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 475,229 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.