JHU Biomedical Engineering Primary Faculty
 Michael I. Miller, Ph.D.Herschel and Ruth Seder Professor Director, Center for Imaging Science
Center for Imaging Science
Clark Hall 301
(410) 516-4594
mim@cis.jhu.edu
http://www.cis.jhu.edu
EducationB.S.E.E. State University of NY at Stony Brook, 1976
M.S.E.E., The Johns Hopkins University, 1978
Ph.D., B.M.E., The Johns Hopkins University, 1983
Michael Miller is a University Gilman Scholar and is the Herschel and Ruth Seder Professor of Biomedical Engineering. Dr. Miller directs the Center for Imaging Science. He received his PhD in biomedical engineering from Johns Hopkins University.Research InterestsMedical image understanding is where speech and language modeling was in 1980. Back then there were few
speech, language and text understanding systems. Most of the greatest work had been focusing on the digital and
acoustic stream; little progress had been made on the linguistics and structural representation of the language itself.
This has all changed, with the entire focus moving away from the acoustic models to the higher level representations
of information. Analogously, today in imaging there is a plethora of magnificent imaging devices of all kinds, at all
scales, at all prices. However, there is little in the way of image understanding systems, systems which bring value
not from the measured picture but from knowledge bases in the world. Think about it, in the context of Medical
image reconstruction, could it really be that there is more information from a single MRI scan than in all of the
books that Neuroscientists and Radiologists have catalogued since the Renaissance era of da Vinci and
Michelangelo? Why then are there no examples of medical imaging devices which inject such information into their
modality.
We would argue that the difficulty is that Biological shape is exquisitely variable, and we have had few methods for
computing metric distance between real-world shapes and geometries, and few tools for measuring closeness of the
geometric representation of normal and abnormal anatomical and biological shapes. Without such metrics there are
no structured ways to build models of real-world knowledge and insert that information into the Medical image
reconstruction algorithms. This is all changing now with the emergence of Grenander's metric pattern theory, a
formalism which provides methods for constructing metric space models of the complex shapes of the world. In the
context of Medical Imaging, this enterprise is coming to be called Computational Anatomy.
Biomedical engineering students Faisal Beg, Christian d'Avignon, and Marc Vaillant are currently engaged in the
characterization of such metrics in human populations, studying the shapes and structures of the human brain. As
well, diseased populations including Schizophrenics and normal and abnormal aging populations are being
characterized. With the completion of their work we should envision medical devices which “Image on the
Geometries of the Human Body.”
Selected PublicationsU. Grenander and M. I. Miller, "Computational Anatomy: An Emerging Discipline", Quart. App. Math., 1998,
vol. 56, pp. 617-694.
M.I. Miller and L. Younes, "Group Actions, Homeomorphisms, and Matching: A General Framework,"
International Journal of Computer Vision, Volume 41, No 1/2, pages 61-84, January, 2001.
John G. Csernansky, Lei Wang, Sarang Joshi, J. Philip Miller, Mokhtar Gado, Daniel Kido, Daniel McKeel, John C.
Morris, Michael I. Miller, "Early DAT is Distinguished from Aging by High Dimensional Mapping of the
Hippocampus," Neurology, 1,1636-1643, 2000.
Publications SearchFrom Pub Med | Google Scholar Profile
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