Jump to content

User:Mim.cis/sandbox/Vitae-Version2

From Wikipedia, the free encyclopedia
Michael I. Miller
File:??.jpg
Michael Miller in 2010.
Born1955 (age 68–69)
Brooklyn, New York, United States
Nationality American
Alma materThe State University of New York at Stony Brook
The Johns Hopkins University
Known forComputational anatomy[3]

LDDMM[4]

Diffeomorphometry and BrainGPS[5]
SpouseElizabeth Patton Miller
AwardsPresidential Young Investigator Award


Herschel and Ruth Seder Chair in Biomedical Engineering[1]


Johns Hopkins University Gilman Scholar [2].
Scientific career
FieldsBiomedical Engineering
Neuroscience
Pattern Theory
InstitutionsWashington University in St. Louis
The Johns Hopkins University Center for Imaging Science
The Johns Hopkins University
ThesisStatistical Coding of Complex Speech Stimuli in the Auditory Nerve (1983)
Doctoral advisorMurray B. Sachs
Other academic advisorsEric. D. Young
Doctoral studentsBadrinath Roysam
Anuj Srivastava
Sarang Joshi
Aaron Lanterman
Gary Christensen
Anqi Qiu
Marc Vaillant
Aastha Jain
Dimitri Bitouk
Jun Ma
Jianyang Zhang
Yajing Zhang
Xiaoying Tang
Dan Wu
Daniel Tward
Kwame Kutten
Sue Kulason
Brian Lee
Website[1]

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[6]. 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

[edit]

Miller received his Bachelor of Engineering degree in 1976 from The State University of New York at Stony Brook, and then joined the Department of Biomedical Engineering at the Johns Hopkins University, where he received his Master of Science degree in Electrical and Computer Engineering in 1978 and a Ph.D. degree in Biomedical Engineering in 1983.[7]

After completing his graduate studies, Miller joined the Biomedical Computer Laboratory[8] 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. [9]. On two ocassions during this period, Miller was also a visiting professor at Brown University Division of Applied Mathematics, where he worked with Ulf Grenander on image analysis.

In 1998 Miller joined the Department of Biomedical Engineering [2] 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 [3], one of the nations premier groups in image analysis. In March of 2011, Miller was appointed by President Ronald J. Daniels and then Provost Lloyd B. Minor as one of 17 inaugural University Gilman Scholars selected from all divisions of the University [10], 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

[edit]

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 [11] at Johns Hopkins University. Fellow graduate students were Patrick Barta, Pete Bernardin, Dan Gibson, Thomas Schalk, Herbert Voigt, Raimond L. Winslow.

With Sachs and Young, Miller focused on rate - timing population codes of complex, speech features including voice-pitch [12] and consonant-vowel syllables [13] encoded in the discharge patterns across the entire Auditory nerve. These neural codes formed the basis for the discussions at the 1982 New York Academy of Science [14] meeting on efficacy and timeliness of Cochlear implants.

Early Years in Medical Imaging at Washington University

[edit]

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 [15] [16]. This became one of the main approaches for controlling noise artifacts in iterations of the Shepp-Vardi algorithm[17]in the context of low count, time-of-flight emission tomography, and it was during this period that Miller met Lawrence (Larry) Shepp. Miller subsequently visited Bell Laboratory several times to speak as part of the Henry Landau seminar series, with Shepp remaining a mentor and friend throughout Miller's career.

The Pattern Theory Era and Computational Anatomy

[edit]

Miller joined the Pattern Theory group at Brown University in 1993 during a sabattical from Washington University to work with Ulf Grenander on problems in image analyis within the Bayesian framework of Markov random field models. Their first noteworthy work together was on the ergodic properties of jump-diffusion processes for inference in hybrid parameter spaces, which was delivered by Miller at the Journal of the Royal Statistical Society as a discussed paper. [18] This was the first class of random sampling algorithms defined with ergodic properties proven to sample from distributions supported across discrete sample spaces and supported over the continuum, likening it to the extremely popular Gibb's sampler of Geman and Geman[19] as well as more classical diffusion based samplers associated to Langevin dynamics.

They continued their work together for approximately 15 years after the first sabattical year, with Miller supported as a visiting professor in the Division of Applied Mathematics at Brown. The Millers joined the Grenanders several summers in Sweden at the Grenanders' house in Vastervik, and staying at the Mittag-Leffler Institute in Stockholm as well. During this period, the two worked on linguistic structures and Unification grammars attempting to extend the random field models of Pattern theory to probabilistic structures that exploit the conditional probabilities of directed acyclic graphs.[20] Grenander had modeled the generative theories of Noam Chomsky having published on entropies of Context-Free languages[21] as part of his early work with the Brown Linguistics group, this providing an early bridge for Miller to the Grenander pattern theory school through his own efforts on entropies of the super-critical branching processes.[22]

The two started their work together on human shape and form during this period. Grenander had already published influential papers on deformable templates for hands[23]; Miller published with Gary Christensen and Richard Rabbitt on the use of flows for dense template or image matching.[24][25] Computational anatomy was introduced as a formal theory of human shape and form in the May 1997 lecture given by Grenander and Miller at the 50th Anniversary of the Division of Applied Mathematics at Brown University,[26] and subsequent publication.[27] In the same year with Paul Dupuis[28], they published the foundational paper establishing the necessary Sobolev smoothness conditions requiring vector fields to have strictly greater than two generalized derivatives (in space of 3-dimensions) which are square-integrable, to ensure that smooth submanifold shapes are carried smoothly by the flows.[29]

Collaborating with the French on Shape and Form

[edit]

David Mumford appreciated the smoothness results on existence of flows, and encouraged Miller and the French group at École normale supérieure de Cachan who had been working independently to collaborate. In 1998, Mumford organized the Trimestre "Questions Mathématiques en Traitement du Signal et de l'Image" at the Institute Henri Poincaré, out of which emerged the collaborations between Miller, Trouve and Younes on shape which continue to date. The earliest equations on geodesics generalizing the Euler equation on fluids supporting localized scale (compressible) appeared,[30],the diffeomorphometry metric first appeared implying a metric structures for shape and form,[31] and subsequenlty the conservation of momentum law.[32] This completed the generative theory of Computational anatomy since the random orbit model could be defined as shoots of the geodesic. The Hamiltonian formalism was subsequently described.[33]

Contributions to Brain Mapping

[edit]

The Computational anatomy framework establishing high-dimensional brain mapping at the morphological scale of MRI became the defacto standard for cross-section analyses of populations being studied via MRI at 1 mm. Numerous codes now exist for diffeomorphic template or atlas mapping, with many codes now available such as ANTS,[34] DARTEL,[35] DEMONS,[36] LDDMM,[37] StationaryLDDMM[38], all actively used codes for constructing correspondences between coordinate systems based on sparse features and dense images.

While at Washington University, Miller started a long-term research program with John Csernansky[39], working on the 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. [40] This was one of the papers influencing the recommendations of the working group to include MR based morphometry markers of medial temporal lobe structures for consideration in clinical diagnosis.

In 2014, with Marilyn Albert and Laurent Younes, the Johns Hopkins University BIOCARD[41], team led by Marilyn Albert 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[42], and subsequently that this could be measured via MRI in clinical populations upwards of 10 years before clinical symptom[43]. This has the potential to impact clinical treatment of the disease.

See also

[edit]

Selected works

[edit]

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

[edit]
  1. ^ "Herschel and Ruth Seder Chair in Biomedical Engineering". The Johns Hopkins University.
  2. ^ "University taps 17 as inaugural Gilman Scholars". The JHU Gazette. Johns Hopkins. 2011.
  3. ^ Grenander, Ulf; Miller, Michael I. (December 1998). "Computational Anatomy: An Emerging Discipline". Quarterly of Applied Mathematics. 56 (4): 617-694.
  4. ^ Beg, M.F.; Miller, M.I.; Trouve, A.; Younes, L. (2005). "Computing large deformation metric mappings via geodesic flows of diffeomorphisms" (PDF). International Journal of Computer Vision. 61 (2): 139–157.
  5. ^ Miller, M.I.; Trouve, A.; Younes, L. (2014). "Diffeomorphometry and Geodesic Positioning Systems for Human Natomy". Technology (Singapore World Science). 2 ((1)): 36. PMID 24904924.
  6. ^ "University taps 17 as inaugural Gilman Scholars". The JHU Gazette. Johns Hopkins. 14 March 2011.
  7. ^ Miller, Michael I. (1983). Statistical coding of complex stimuli in the auditory nerve (PhD thesis). The Johns Hopkins University.
  8. ^ "Institute for Biomedical Computing". Digital Commons@Becker.
  9. ^ "Newton R. and Sarah Louisa Glasgow Wilson Professorship in Engineering" (PDF).
  10. ^ "University taps 17 as inaugural Gilman Scholars". The JHU Gazette. Johns Hopkins. 14 March 2011.
  11. ^ "Neural Encoding Laboratory".
  12. ^ Miller, M.I.; Sachs, M.B. (June 1984). "Representation of voice pitch in discharge patterns of auditory-nerve fibers". Hearing Research. 14 ((3)): 257–279. PMID 6480513.
  13. ^ Miller, M.I.; Sachs, M.B. (1983). "Representation of stop consonants in the discharge patterns of auditory-nerve fibers". JASA. 74 ((2)): 502–517. doi:10.1121/1.389816.
  14. ^ Sachs, M.B.; Young, E.D.; Miller, M.I. (June 1983). "Speech Encoding in the Auditory Nerve: Implications for Cochlear Implants". Annals of the New York Academy of Sciences: 94–114. doi:10.1111/j.1749 6632.1983.tb31622.x. {{cite journal}}: Check |doi= value (help)
  15. ^ Snyder, Donald L.; Miller, Michael I. (1985). "On the Use of the Method of Sieves for Positron Emission Tomography". IEEE Transactions on Medical Imaging. NS-32(5): 3864–3872. doi:10.1109/TNS.1985.4334521.
  16. ^ Snyder, D.L.; Miller, M.I.; Thomas, L.J.; Politte, D.G. (1987). "Noise and edge artifacts in maximum-likelihood reconstructions for emission tomography". IEEE Trans. on Medical Imaging. 6 ((3)): 228–238.
  17. ^ Shepp, L.; Vardi, Y. (1982). "Maximum likelihood reconstruction for emission tomography". IEEE Transactions Medical Imaging. 1 (2): 113–122. doi:10.1109/TMI.1982.4307558. PMID 18238264.
  18. ^ Grenander, U.; Miller, M.I. (1994). "Representations of Knowledge in Complex Systems". Journal of the Royal Statistical Society Series B (methodological). 56 (4): 549–603.
  19. ^ S. Geman; D. Geman (1984). "Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images". IEEE Transactions on Pattern Analysis and Machine Intelligence. 6 (6): 721–741. doi:10.1109/TPAMI.1984.4767596.
  20. ^ Mark, K.; Miller, M.I.; Grenander, U. "Constrained Stochastic Language Models". In Shepp, L.; Levinson, S.E. (eds.). The IMA Volumes in Mathematics and its Applications: Image Models and their Speech Model Cousins. Springer, New York. pp. 131–141. ISBN 978-1-4612-4056-3.
  21. ^ Grenander, U. (January 1981). Abstracat Inference. New York: John Wiley and Sons. ISBN 0471082678.
  22. ^ Miller, M.I.; O'Sullivan, J. A. (July 1992). "Entropies and combinatorics of random branching processes and context-free languages". IEEE Transactions on Information Theory. 38 (4): 1292–1310. doi:10.1109/18.144710.
  23. ^ Grenander, U.; Chow, Y-S; Keenan, D. (1991). Hands: a pattern theoretic study of biological shapes. New York: Springer-Verlag. ISBN 0387973869.
  24. ^ Christensen, G.E.; Miller, M.I.; Rabbitt, R.D. (March 24–26, 1993). Prince, J.; Runolfsson (eds.). "A deformable neuroanatomy based on viscous fluid mechanics". Proceedings of the 1993 Conference on Information Science and Systems. Baltimore, Maryland: Johns Hopking University: 211–216.{{cite journal}}: CS1 maint: date format (link)
  25. ^ Christensen, G.E.; Rabbitt, R.D.; Miller, M.I. (1996). "Deformable templates using large deformation kinematics". IEEE Transactions on Image Processing. 5 (10): 1435–1447. doi:10.1109/83.536892.
  26. ^ Walter Freiberger (ed.). "Current and Future Challenges in the Applications of Mathematics". Quarterly of Applied Mathematics.
  27. ^ Grenander, Ulf; Miller, M.I. (December 1998). "Computational Anatomy: An Emerging Discipline" (PDF). Quarterly of Applied Mathematics. LVI (4): 617–694.
  28. ^ Dupuis, Paul. "IBM Professor of Applied Mathematics". Applied Mathematics. Brown University.
  29. ^ Dupuis, P.; Grenander, U.; Miller, M.I. (September 1998). "Variational Problems on Flows of Diffeomorphisms for Image Matching". Quarterly of Applied Mathematics. 56 (3): 587–600.
  30. ^ Miller, M.I.; Trouve, A.; Younes, L. (2002). "On the Metrics and Euler-Lagrange Equations of Computational Anatomy". Annual Review of Biomed. Engineering. 4: 375–405.
  31. ^ Miller, M.I.; Younes, L. (2001). "Group Actions, Homeomorphisms, And Matching: A General Framework". International Journal of Computer Vision. 41 (1–2): 61–84. doi:10.1023/A:1011161132514.
  32. ^ Miller, M.I.; Trouve, A.; Younes, L. (31 January 2006). "Geodesic shooting for computational anatomy". Internation Journal of Computer Vision. 24 ((2)): 209–228. doi:10.1007/s10851-005-3624-0.
  33. ^ Miller, M.I.; Trouve, A.; Younes, L. (December 2015). "Hamiltonian Systems and Optimal Control in Computational Anatomy: 100 Years Since D'Arcy Thompson". Annual Review of Biomedical Engineering. 17: 447–509. doi:10.1146/annurev-bioeng-071114-040601.
  34. ^ "stnava/ANTs". GitHub. Retrieved 2015-12-11.
  35. ^ Ashburner, John (2007-10-15). "A fast diffeomorphic image registration algorithm". NeuroImage. 38 (1): 95–113. doi:10.1016/j.neuroimage.2007.07.007. PMID 17761438.
  36. ^ "Software - Tom Vercauteren". sites.google.com. Retrieved 2015-12-11.
  37. ^ "NITRC: LDDMM: Tool/Resource Info". www.nitrc.org. Retrieved 2015-12-11.
  38. ^ "Publication:Comparing algorithms for diffeomorphic registration: Stationary LDDMM and Diffeomorphic Demons". www.openaire.eu. Retrieved 2015-12-11.
  39. ^ Csernansky, J.G. "Department of Psychiatry and Behavioral Sciences".
  40. ^ Csernansky, J.G.; Wang, L.; Swank, J.; Miller, JP; Gado, M.; McKeel, D.; Miller, M.I.; Morris, J.C. (15 April 2005). "Preclinical detection of Alzheimer's disease: hippocampal shape and volume predict dementia onset in the elderly". Neuroimage. 25 (3): 783–792. doi:10.1016/j.neuroimage.2004.12.036. PMID 15808979.
  41. ^ Albert, M. S. "BIOCARD: Predictors of Cognitive Decline Among Normal Individuals". Alzheimer's Disease Research Center. Johns Hopkins University School of Medicine.
  42. ^ Miller, M.I.; Younes, L.; Ratnanather, J.T.; Brown, T.; Trinh, H.; Postal, E.; Lee, D.S.; Wang, M.C; Mori, S.; Obrien, R.; Albert, M.; Research Team, BIOCARD (16 September 2013). "The diffeomorphometry of temporal lobe structures in preclinical Alzheimer's disease". Neuroimage Clinical. 3 (352–360). doi:10.1016/j.nicl.2013.09.001.
  43. ^ Younes, L.; Albert, M.; Miller, M.I.; Research Team, BIOCARD (21 April 2014). "Inferring changepoint times of medial temporal lobe morphometric change in preclinical Alzheimer's disease". Neuroimage Clinical. 5: 178–187. PMID 25101236.
[edit]

{{Commons category|Michael I. Miller}


Category:Living people Category:Stony Brook University alumni Category:Johns Hopkins University alumni Category:Johns Hopkins University faculty Category:American electrical engineers Category:American biomedical engineers Category:Bioinformaticians Category:Jewish scientists Category:1955 births Category:Fellows of the American Institute for Medical and Biological Engineering

Retrieved from "https://en.wikipedia.org/w/index.php?title=User:Mim.cis/sandbox/Vitae-Version2&oldid=744374313"