2020 - IEEE Fellow For contributions to medical imaging, brain mapping, and computational anatomy
Michael Miller mostly deals with Internal medicine, Neuroscience, Magnetic resonance imaging, Artificial intelligence and Brain mapping. His Internal medicine research includes elements of Endocrinology and Cardiology. His Neuroscience research incorporates elements of Alzheimer's disease, White matter and Diffusion MRI.
As part of one scientific family, Michael Miller deals mainly with the area of Magnetic resonance imaging, narrowing it down to issues related to the Nuclear medicine, and often Pattern matching. His Artificial intelligence study incorporates themes from Atlas, Atlas, Computer vision and Pattern recognition. His Brain mapping research integrates issues from Cerebral cortex, Neuroanatomy, Central nervous system and Cortex.
Michael Miller mainly investigates Artificial intelligence, Internal medicine, Computer vision, Neuroscience and Pattern recognition. Michael Miller combines subjects such as Large deformation diffeomorphic metric mapping, Diffeomorphism and Atlas with his study of Artificial intelligence. His Internal medicine research includes elements of Endocrinology and Cardiology.
He has included themes like White matter, Magnetic resonance imaging and Diffusion MRI in his Neuroscience study.
His main research concerns Internal medicine, Artificial intelligence, Cardiology, Disease and Pattern recognition. His research in Internal medicine intersects with topics in Eicosapentaenoic acid and Endocrinology. His Artificial intelligence research is multidisciplinary, relying on both Machine learning, Missing data and Neuroimaging.
Michael Miller is interested in Myocardial infarction, which is a field of Cardiology. The study incorporates disciplines such as Statin and Relative risk reduction in addition to Hypertriglyceridemia. His research is interdisciplinary, bridging the disciplines of Diabetes mellitus and Statin.
Michael Miller mainly investigates Internal medicine, Artificial intelligence, Disease, Cardiology and Pattern recognition. Particularly relevant to Triglyceride is his body of work in Internal medicine. His Artificial intelligence study combines topics in areas such as Machine learning and Missing data.
In general Disease study, his work on Dementia, Cardiovascular health and Organ system often relates to the realm of Health benefits, thereby connecting several areas of interest. His Cardiology research is multidisciplinary, incorporating perspectives in Platelet aggregation inhibitor, Placebo and Reduction. His study on Automated segmentation is often connected to Nissl body as part of broader study in Pattern recognition.
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Computing Large Deformation Metric Mappings via Geodesic Flows of Diffeomorphisms
M. Faisal Beg;Michael I. Miller;Alain Trouvé;Laurent Younes.
International Journal of Computer Vision (2005)
Deformable templates using large deformation kinematics
G.E. Christensen;R.D. Rabbitt;M.I. Miller.
IEEE Transactions on Image Processing (1996)
Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template
Susumu Mori;Susumu Mori;Kenichi Oishi;Hangyi Jiang;Li Jiang.
Random Point Processes in Time and Space
Donald L. Snyder;Michael I. Miller.
Computational anatomy: an emerging discipline
Ulf Grenander;Michael I. Miller.
Quarterly of Applied Mathematics (1998)
Representations of Knowledge in Complex Systems.
Ulf Grenander;Michael I. Miller.
Journal of the royal statistical society series b-methodological (1994)
Volumetric transformation of brain anatomy
G.E. Christensen;S.C. Joshi;M.I. Miller.
IEEE Transactions on Medical Imaging (1997)
Landmark matching via large deformation diffeomorphisms
S.C. Joshi;M.I. Miller.
IEEE Transactions on Image Processing (2000)
Mathematical textbook of deformable neuroanatomies
Michael I. Miller;Gary E. Christensen;Yali Amit;Ulf Grenander.
Proceedings of the National Academy of Sciences of the United States of America (1993)
Hippocampal morphometry in schizophrenia by high dimensional brain mapping
John G. Csernansky;Sarang Joshi;Lei Wang;John W. Haller.
Proceedings of the National Academy of Sciences of the United States of America (1998)
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