*Note the day change. This talk is on a Monday.
Strategies for motion artifact correction in brain MRI
Head motion during MRI of the brain is widely recognized as a major problem in both clinical practice and neuroimaging research. Just a few millimetres of movement can easily cause artifacts when a single image is encoded over several minutes. Motion during sensitive time series measurements such as functional MRI can also cause inconsistencies that image registration does not compensate for.
In this talk I will discuss complementary strategies we are working on for detection, measurement, and correction of head motion artifacts: 1) optical head motion tracking; 2) machine learning to extract relevant information from unchanged sequences; 3) modifying sequences to acquire MR-signal “navigators” that provide information about head motion and associated secondary effects, e.g., on the B0 field.
Dr. Robert Frost has a background in MRI physics, pulse sequence development, and image reconstruction for improving image quality in clinical and neuroscientific applications. His PhD research at the FMRIB Centre, University of Oxford, focused on high-resolution, low-distortion diffusion-weighted MRI and related motion navigation. The techniques they developed have been incorporated in Siemens product sequences. During his postdoctoral training at the FMRIB Centre, he began working on implementing real-time, prospective head motion correction in clinical research sequences as part of a collaboration with André van der Kouwe. In 2016, he moved to the Athinoula A. Martinos Center at Massachusetts General Hospital (MGH) to continue working on motion correction in MR and he is now an Assistant Professor of Radiology at MGH and Harvard Medical School.