Scientific computing in medical image reconstruction

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Medical image reconstruction is the foundation for medical imaging; without accurate reconstruction, medical images contain errors that make diagnosis difficult or impossible.  Yet, there are many frontiers in medical image reconstruction that are untouched by the field of scientific computing.  This proposal aims at addressing two exciting medical image reconstruction issues, one in magnetic resonance imaging (MRI), and one in computed tomography (CT).Intra-echo MRI motion correction looks at ways to use a motion-tracking device with an MR scanner to improve image reconstruction.  Patient motion, such as Parkinsonian tremors, can corrupt the sensitive images that are used to diagnose and analyse ailments like multiple sclerosis, strokes, and other cerebrovascular diseases.  We propose that the intelligent use of motion-tracking data can compensate for that motion.The second project involves the development of reconstruction methods for portable CT scanners.  Researchers in nanotechnology are working on flexible arrays of x-ray emitters and detectors.  Using these arrays, we forsee a new breed of portable CT scanners that can be deployed right at the scene of an accident.  However, these devices have interesting reconstruction challenges that must be addressed before a prototype can be built.We propose the use of scientific computing to address these challenges.