Abstract #0563
Image quality transfer: exploiting bespoke high-quality data to enhance everyday acquisitions
Daniel C. Alexander 1 , Darko Zikic 2 , Viktor Wottschel 3 , Jiaying Zhang 1 , Hui Zhang 1 , and Antonio Criminisi 2
1
Dept. Computer Science, University College
London, London, London, United Kingdom,
2
Microsoft
Research, Cambridge, United Kingdom,
3
Institute
of Neurology, University College London, London, United
Kingdom
Learning the low-level structure of images from
high-quality bespoke data sets can substantially improve
the content of images reconstructed from more everyday
acquisitions. The abstract presents a method that
achieves this and demonstrates it using diffusion MRI
data from the human connectome project.
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