Combined motion-compensated and super-resolution image reconstruction to improve magnetic resonance imaging of the upper abdomen

Aims of the project
Demonstrate the benefits of using respiratory motion modelling as a means to improve the image quality and imaging efficiency of clinical abdominal MRI.
Investigate methods of generating motion surrogate signals from reduced data to speed up the acquisition and investigate the impact of using these signals on the motion models and motion corrected images.
Investigate the effect of reducing the number of samples of the 'model slices' on the motion models and motion corrected images.
Brief description of the project background
A motion modelling framework has recently been demonstrated (by Dr Jamie McClelland) that can model 3D motion from partial image data, such as 2D image slices. The image slices ('model slices') are each acquired at multiple points within the breathing cycle. The model is parameterised by one or more motion surrogate signals that are derived from a 'surrogate slice', which is acquired at a fixed location.
The motion model can be used for motion compensated image reconstruction, to produce a motion corrected 3D image, with or without super-resolution (SR) reconstruction. The framework has, so far, only been applied in the lung, using CT and MR imaging. This project will test its application to abdominal MRI, in particular, to liver imaging.
Abdominal MRI typically involves the patient holding their breath repeatedly as each set of images is acquired. This limits the image quality attainable, complicates the acquisition process, reduces the imaging efficiency (due to recovery periods between breath-holds) and can be difficult or uncomfortable for patients.
This project will take a typical MR pulse sequence that is used clinically for structural imaging of the liver and modify it so that signals are acquired that can be used to estimate the motion field across the liver. This field will be used to correct for the motion that occurs during the acquisition. Super-resolution reconstructions will be compared between the images acquired with breath-holds and those acquired during free-breathing and motion-corrected.