Alexandra R. Morgan1, 2, Arousa Ali1, Penny L. Hubbard1, 2, Geoff JM Parker1, 2, Marietta LJ Scott3, Simon S. Young3, Lars E. Olsson4, Caleb Roberts1, 2, Josephine H. Naish1, 2
1Imaging Science, School of Cancer and Enabling Sciences, Manchester Academic Health Science Centre, The University of Manchester, Manchester, Greater Manchester, United Kingdom; 2Biomedical Imaging Institute, The University of Manchester, Manchester, Greater Manchester, United Kingdom; 3AstraZeneca R&D, Alderley Park, Macclesfield, United Kingdom; 4AstraZeneca R&D, Mlndal, Sweden
Pixel-wise analysis of pulmonary images acquired using oxygen-enhanced magnetic resonance imaging (OE-MRI) is challenging because of non-linear changes in shape and size of the lung during free breathing. A new non-linear image registration method is presented here, utilizing a lung motion model derived on a subject-by-subject basis from serial structural imaging. The method is shown to be advantageous when compared with no registration and with a 1-D linear registration, reducing error in fitting baseline T1 maps post-registration and alleviating motion induced signal intensity fluctuations in dynamic OE-MRI of oxygen wash-in/-out.