Motion artifact correction in ASL images: an improved automated procedure

Arterial Spin Labelling (ASL) is a perfusion MRI technique with tremendous applications in the study of biological markers and prognostic factors of brain tumors and in the assessment of neural diseases; moreover, it is completely non-invasive as it uses the magnetically inverted blood of the patient as an endogenous tracer. Unfortunately this powerful method is only viable in very limited conditions due to its extreme sensitivity to artifacts originated by head motion, that are not effectively addressed by the current software solutions. This paper presents a motion correction procedure that addresses this issue and provides improved solutions to enhance ASL images of the brain in presence of severe head motion. Experimental results run on a motion-affected pCASL dataset show the concept and demonstrate the superiority of our proposed procedure compared to standard 3D registration.