Intuitionistic Fuzzy Position Embedding Transformer for Motion Artefact Correction in Chemical Exchange Saturation Transfer MRI Series

Abstract

Chemical Exchange Saturation Transfer (CEST) Magnetic Resonance Imaging (MRI) is a cutting-edge molecular imaging technique that enables non-invasive in vivo visualization of biomolecules, such as proteins and glycans, with exchangeable protons. However, CEST MRI is prone to motion artefacts, which can significantly reduce its accuracy and reliability. To address this issue, this study proposes an image registration method specifically designed to correct motion artefacts in CEST MRI data, with the objective of improving the precision of CEST analysis. Traditional registration techniques often suffer from premature convergence to local optima, especially in the presence of rigid motion within the ventricular region. The proposed approach leverages an Intuitionistic Fuzzy Set (IFS) position encoding integrated with a multi-head attention mechanism to achieve accurate global registration. A custom loss function is designed based on the properties of IFS position encoding to further enhance the model's motion correction capabilities. Experimental results demonstrate that this method provides a more robust and accurate solution for motion artefact correction in CEST MRI, offering new potential for improving the precision of CEST imaging in clinical and research settings.