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

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.

Proactive Evolutionary Algorithms for Dynamic Optimization Problems
Presentation slides that outline the three anticipation strategies used in proactive evolutionary algorithms designed for dynamic optimization problems.
pfi_slides.pdf
Compressed Sensing for Fast 31P-MRSI of Brain Tumors and 1H-MRSI of Mild Cognitive Impairment in Parkinson’s Disease
Presentation slides that explain compressed sensing accelerated phosphorus MR spectroscopic imaging of brain tumors, and preliminary findings in proton MR spectroscopic imaging of Parkinson's disease with mild cognitive impairment.
NMG_Workshop_EOI.pdf

Ozturk-Isik, Esin; Marshall, Ian; Filipiak, Patryk et al. (2017). Data from: Workshop on reconstruction schemes for magnetic resonance data: summary of findings and recommendations [Dataset]. Dryad. https://doi.org/10.5061/dryad.gg5td