Michael I. Miller

Michael Ira Miller (born 1955), an American biomedical engineer and neuroscientist is a leading researcher in brain mapping in the field of medical imaging at Johns Hopkins University. Miller is the Hershel Seder Professor of Biomedical Engineering and Johns Hopkins University Gilman Scholar.^[10] Well known for his pioneering work in the field of Computational Anatomy with Ulf Grenander, Miller directs the Johns Hopkins Center for Imaging Science within the Whiting School of Engineering; he is also Co-Director, with Richard L. Huganir, of the Johns Hopkins Kavli Neuroscience Discovery Institute.

Biography

Miller received his Bachelor of Engineering degree from The State University of New York at Stony Brook in 1976. He then joined the Department of Biomedical Engineering at the Johns Hopkins University, where he received his Master of Science degree in Electrical Engineering in 1978 and a Ph.D. degree in Biomedical Engineering in 1983.^[11]

After completing his graduate studies, Miller joined the Biomedical Computer Laboratory^[12] at Washington University in St. Louis to work on Medical imaging with Donald L. Snyder, then chair of Electrical Engineering at Washington University School of Engineering and Applied Science. He then joined the faculty of Electrical Engineering in 1985 and remained on the faculty at Washington University through 1998 as the Newton R. and Sarah Louisa Glasgow Wilson Professor in Engineering.^[13] On several occasions during this period, Miller was a visiting professor at Brown University's Division of Applied Mathematics where he worked with Ulf Grenander on image analysis.

In 1998 Miller joined the Department of Biomedical Engineering at Johns Hopkins University where he has remained as the Herschel and Ruth Seder Professor of Biomedical Engineering and the Director of the Center for Imaging Science, one of the nations premier groups in image analysis. In March 2011, Miller was appointed by President Ronald J. Daniels as one of 17 inaugural University Gilman Scholars selected from all divisions of the University^[14] in recognition of their efforts to uphold the highest ideals of the University in demonstrating distinguised records in research, artistic achievement, creativity, teaching and service.

In 2015, Miller was selected as the Co-director of the newly awarded Kavli Institute for Discovery Neuroscience.

Michael Miller is a fellow of the American Institute for Medical and Biological Engineering, and a senior member of the Institute of Electrical and Electronics Engineers.

Academic career

Neural Coding at Johns Hopkins University

Miller did his doctoral work on neural codes in the Auditory system under the direction of Murray B. Sachs and Eric D. Young in the Neural Encoding Laboratory^[15] at Johns Hopkins University. Fellow graduate students included Patrick Barta,^[16] Pete Bernardin, Dan Gibson, Lisa Hellstrom,^[17] Thomas Schalk, Herbert Voigt,^[18] Raimond L. Winslow.^[19]

With Sachs and Young, Miller focussed on rate-timing population codes of complex, speech features including voice-pitch^[20] and consonant-vowel syllables ^[21] encoded in the discharge patterns across the primary auditory-nerve. These neural codes formed the basis for the discussions at the 1982 New York Academy of Science^[22] meeting on efficacy and timeliness of Cochlear implants.

Medical Imaging at Washington University

Miller's impact in the field of brain mapping in Medical imaging, specifically statistical methods for iterative image reconstruction began in the mid 80's when he joined Donald L. Snyder at Washington University to work on time-of-flight positron emission tomography (PET) systems being instrumented in Michel Ter-Pogossian's group. Working with Snyder, Miller's notable contribution was to stabilize likelihood-estimators of radioactive tracer intensities via the method-of-sieves^[23] .^[24] This became one of the main approaches for controlling noise artifacts in the Shepp-Vardi algorithm^[25] in the context of low count, time-of-flight emission tomography. It was during this period that Miller met Lawrence (Larry) Shepp, and subsequently visited Shepp several times at Bell Labs to speak as part of the Henry Landau seminar series. Shepp remained a mentor and friend throughout Miller's career.

The Pattern Theory Era and Computational Anatomy

During the mid 90's, Miller joined the Pattern Theory group at Brown University and worked with Ulf Grenander on problems in image analyis within the Bayesian framework of Markov random fields. Their first noteworthy project was to establish the ergodic properties of jump-diffusion processes for inference in hybrid parameter spaces, which was presented by Miller at the Journal of the Royal Statistical Society as a discussed paper. ^[26] Significantly, these were the first results on a class of random sampling algorithms with ergodic properties proven to sample from distributions supported across discrete sample spaces and simultaneously over the continuum, likening it to the extremely popular Gibb's sampler of Geman and Geman^[27] as well as more classical diffusion based samplers associated to Langevin dynamics.

Grenander and Miller continued their collaborations for approximately 15 years, starting their work together on human shape and form during this period of sabatticals and visits by Miller to Brown. Grenander had already published influential papers on deformable templates for hands;^[28] Miller, Christensen, and Rabbitt, had published on the use of flows for dense template or image matching.^[29][30] Together, Grenander and Miller introduced Computational anatomy as a formal theory of human shape and form at a joint lecture in May 1997 at the 50th Anniversary of the Division of Applied Mathematics at Brown University,^[31] and subsequent publication.^[32] In the same year with Paul Dupuis,^[33] they published the foundational paper establishing the necessary Sobolev smoothness conditions requiring vector fields to have strictly greater than two, square-integrable, generalized derivatives (in space of 3-dimensions) to ensure that smooth submanifold shapes are carried smoothly by the flows.^[34]

By 2005, the Computational anatomy framework establishing high-dimensional brain mapping via diffeomorphisms at the morphological scale of MRI had become the de facto standard for cross-section analyses of populations studied via 1mm MRI. Codes now exist for diffeomorphic template or atlas mapping, including ANTS,^[35] DARTEL,^[36] DEMONS,^[37] LDDMM,^[38] StationaryLDDMM,^[39] all actively used codes for constructing correspondences between coordinate systems based on sparse features and dense images.

Collaborating with École normale supérieure de Cachan on Shape and Form

David Mumford appreciated the smoothness results on existence of flows, and encouraged collaboration between Miller and the École normale supérieure de Cachan group which had been working independently. In 1998, Mumford organized a Trimestre on "Questions Mathématiques en Traitement du Signal et de l'Image" at the Institute Henri Poincaré; from this emerged the collaboration on shape between Miller, Alain Trouve^[40] and Laurent Younes^[41] which continues to date. They published three significant papers together over the subsequent 15 years; the equations for geodesics generalizing the Euler equation on fluids supporting localized scale or compressibility appearing in 2002,^[42] the conservation of momentum law for shape momentum appearing in 2006,^[43] and the Hamiltonian formalism was summarized in 2015.^[44]

Contributions to nueurodegeneration in brain mapping

During these years, Miller and Csernansky ^[45] had developed a long-term research effort on neuroanatomical phenotyping of Alzheimer's disease, Schizophrenia and mood disorder. In 2005, they published with John Morris an early work on predicting conversion to Alzheimer's disease based on clinically available MRI measurements using the diffeomorphometry technologies.^[46] This was one of the papers that contributed to a deeper understanding of the disorder in it earlier stages and the recommendations of the working group for the first time in 27 years to revise the diagnostic criteria for Alzheimer’s disease dementia.^[47]

In 2009, the Johns Hopkins University BIOCARD^[48] project was initiated, led by Marilyn Albert,^[49] to study preclinical Alzheimer's disease. In 2014, Miller and Younes demonstrated that the original Braak staging of earliest change associated to the entorhinal cortex in the medial temporal lobe could be demonstrated via diffeomorphometry methods in the population of clinical MRI's,^[50] and subsequently that this could be measured via MRI in clinical populations upwards of 10 years before clinical symptom.^[51] This has the potential to impact clinical treatment of the disease.

See also

• Computational anatomy
• LDDMM
• Diffeomorphometry
• Pattern Theory

Selected works

Miller has published two books, the first with Donald L. Snyder, the second with Ulf Grenander.

• Snyder, Donald L.; Miller, Michael I. (1991). Random Point Processes in Time and Space. Springer. ISBN 978-0199297061. 
• Grenander, Ulf; Miller, Michael (2007). Pattern Theory: From Representation to Inference. Oxford University Press. ISBN 978-0199297061. 

References

External links

• Miller's Curriculum Vitae
• Miller's Short Biography
• Center for Imaging Science Website
• Computational anatomy Computational Anatomy website

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