Yawen Huang1, Leandro Beltrachini1, Ling Shao2, and Alejandro Frangi1
1Department of Electronic and Electrical Engineering, The University of Sheffield, Sheffield, United Kingdom, 2 Department of Computer Science and Digital Technologies, Northumbria University, Newcastle, United Kingdom
Multi-modality
MRI protocols are becoming standard in the everyday clinical practise. The
advantages of such acquisitions were shown to be fundamental in a wide range of
applications, such as medical diagnosis and image segmentation. However, the
implementation of these protocols tends to be time-consuming, consisting in one
key limitation. In this paper we address this problem by presenting a novel
method for synthesising any MRI modality from a single acquired image. This is
done using machine learning techniques for dictionary learning. Results show
that our approach can lead to significant performance over the state-of-the-art
methods.
