Automated Author Profile

Benjamin, Arnold J. V.

University of Edinburgh

Current S-Index

0.7

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

0.7

Average Dataset Index per dataset

Total Datasets

1

Total datasets for this author

Average FAIR Score

80.8%

Average FAIR Score per dataset

Total Citations

2

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Data from: Workshop on reconstruction schemes for magnetic resonance data: summary of findings and recommendations (Version: 1)

The high-fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data is essential for simultaneously improving patient care, accuracy in diagnosis and quality in clinical research. Sponsored by the Royal Society through the Newton Mobility Grant Scheme, we held a half-day workshop on reconstruction schemes for MR data on 17 August 2016 to discuss new ideas from related research fields that could be useful to overcome the shortcomings of the conventional reconstruction methods that have been evaluated to date. Participants were 21 university students, computer scientists, image analysts, engineers and physicists from institutions from six different countries. The discussion evolved around exploring new avenues to achieve high resolution, high quality and fast acquisition of MR imaging. In this article, we summarize the topics covered throughout the workshop and make recommendations for ongoing and future works.

Authors

  • Ozturk-Isik, Esin ;
  • Marshall, Ian ;
  • Filipiak, Patryk ;
  • Benjamin, Arnold J.V. ;
  • Ones, Valia Guerra ;
  • Ramón, Rafael Ortiz ;
  • Valdés Hernández, Maria del C. ;
  • Benjamin, Arnold J. V.
2 Citations0 Mentions81% FAIR1.1 Dataset Index
10.5061/dryad.gg5td2017