Michael I. Miller

Miller received his Bachelor of Engineering from The State University of New York at Stony Brook in 1976, followed by a Master of Science degree in 1978 and PhD in biomedical engineering in 1983, both from the Johns Hopkins University.{{Cite news|url=https://www.hopkinsmedicine.org/news/media/releases/michael_miller_named_director_of_biomedical_engineering_|title=Michael Miller Named Director of Biomedical Engineering - 06/30/2017|access-date=2017-12-09|language=en}}{{Cite web|url=http://www.cis.jhu.edu/faculty/cvs/CV_Miller_2016-07-19.pdf|title=Curriculum Vitae, Michael I. Miller}}

He completed postdoctoral research on medical imaging at Washington University in St. Louis with Donald L. Snyder, then chair of the Electrical Engineering department. In 1985, he joined the faculty of Electrical Engineering at Washington University, where he was later named the Newton R. and Sarah Louisa Glasgow Wilson Professor in Engineering.{{cite web|title=Newton R. and Sarah Louisa Glasgow Wilson Professorship in Engineering|url=http://ese.wustl.edu/ContentFiles/AboutTheDepartment/EndowedProfessorships/Wilson.pdf}}{{Cite web|url=http://pages.jh.edu/~gazette/julsep98/aug3198/31newfac.html|title=The Johns Hopkins Gazette: August 31, 1998|website=pages.jh.edu|access-date=2019-01-02}} During his early years at Washington University, Miller received the Presidential Young Investigator Award.{{Cite web|url=http://www.cis.jhu.edu/faculty/cvs/CV_Miller_2016-07-19.pdf|title=Curriculum Vitae, Michael I. Miller}} From 1994 to 2001, 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 as the director of the Center for Imaging Science.{{Cite web|url=http://pages.jh.edu/~gazette/julsep98/aug3198/31newfac.html|title=The Johns Hopkins Gazette: August 31, 1998|website=pages.jh.edu|access-date=2019-01-02}} He was later named the Herschel and Ruth Seder Professor of Biomedical Engineering, and was appointed by Johns Hopkins University President Ronald J. Daniels as one of 17 inaugural University Gilman Scholars in 2011.{{Cite web|url=https://hub.jhu.edu/at-work/2017/06/30/michael-miller-named-director-of-biomedical-engineering/|title=Michael Miller named director of Biomedical Engineering|date=2017-06-30|website=The Hub|language=en|access-date=2019-01-02}}{{Cite web|url=https://professorships.jhu.edu/professorship/herschel-and-ruth-seder-chair-in-biomedical-engineering/|title=Herschel and Ruth Seder Chair in Biomedical Engineering|website=Named Deanships, Directorships, and Professorships|language=en-US|access-date=2019-01-02}} In 2015, Miller became the co-director of the newly established Kavli Institute for Discovery Neuroscience.{{Cite news|url=https://engineering.jhu.edu/news/2015/10/02/bmes-michael-miller-co-director-of-new-kavli-neuroscience-discovery-institute-at-the-johns-hopkins-university/#.WixlDEqnE2x|title=Research: New Kavli Neuroscience Discovery Institute at The Johns Hopkins University {{!}} Johns Hopkins Whiting School of Engineering|date=2015-10-02|work=Johns Hopkins Whiting School of Engineering|access-date=2017-12-09|language=en-US}} In 2017, Miller was named the Massey Professor and Director of the Department of Biomedical Engineering at the Johns Hopkins University.{{Cite web|url=https://www.bme.jhu.edu/people/complete-faculty/|title=Complete Faculty|website=Johns Hopkins Department of Biomedical Engineering|language=en-US|access-date=2019-01-02}} In 2019, he was elected as a IEEE Fellow.{{Cite web|url=https://www.ieee.org/membership/fellows/index.html|title=About the IEEE Fellow Program|website=IEEE|access-date=2019-12-09}}

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{{cite web|title = Neural Encoding Laboratory| url=http://www.hopkinsmedicine.org/otolaryngology/research/neural_encoding/neural_encoding_lab.html}} at Johns Hopkins University. With Sachs and Young, Miller focused on rate-timing population codes of complex features of speech including voice-pitch{{cite journal|last1=Miller|first1=M.I.|last2=Sachs|first2=M.B.|title=Representation of voice pitch in discharge patterns of auditory-nerve fibers|journal=Hearing Research|date=June 1984|volume=14|issue=3|pages=257–279|pmid=6480513|doi=10.1016/0378-5955(84)90054-6|s2cid=4704044}} and consonant-vowel syllables {{cite journal|last1=Miller|first1=M.I.|last2=Sachs|first2=M.B.|title=Representation of stop consonants in the discharge patterns of auditory-nerve fibers| journal= The Journal of the Acoustical Society of America|date=1983|volume=74|issue=2|pages=502–517|doi=10.1121/1.389816|pmid=6619427|bibcode=1983ASAJ...74..502M}} encoded in the discharge patterns across the primary auditory nerve. These neural codes were one of the scientific works discussed as the strategy for neuroprosthesis design at the 1982 New York Academy of Science{{cite journal|last1=Sachs|first1=M.B.|last2=Young|first2=E.D.|last3=Miller|first3=M.I.|title=Speech Encoding in the Auditory Nerve: Implications for Cochlear Implants|journal=Annals of the New York Academy of Sciences|date=June 1983|pages=94–114|doi=10.1111/j.1749-6632.1983.tb31622.x|pmid=6575675|volume=405|issue=1|bibcode=1983NYASA.405...94S|s2cid=46256845}} meeting on the efficacy and timeliness of Cochlear implants.

Miller's work in the field of brain mapping via Medical imaging, specifically statistical methods for iterative image reconstruction, began in the mid 1980s 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. With Snyder, Miller worked to stabilize likelihood-estimators of radioactive tracer intensities via the method-of-sieves{{Cite journal|title = The Use of Sieves to Stabilize Images Produced with the EM Algorithm for Emission Tomography |journal = IEEE Transactions on Nuclear Science|date = 1985 |pages =3864–3872|volume = NS-32(5) |issue = 5|doi= 10.1109/TNS.1985.4334521|first2 = Michael I.|last2 = Miller|first1 = Donald L.|last1 = Snyder|bibcode = 1985ITNS...32.3864S|s2cid = 2112617}}

.{{cite journal|last1=Snyder|first1=D.L.|last2=Miller|first2=M.I.|last3=Thomas|first3=L.J.|last4=Politte|first4=D.G.|title=Noise and edge artifacts in maximum-likelihood reconstructions for emission tomography|journal=IEEE Transactions on Medical Imaging|date=1987|volume=6|issue=3|pages=228–238|doi=10.1109/tmi.1987.4307831|pmid=18244025|s2cid=30033603}}

This became one of the approaches

for controlling noise artifacts in the Shepp-Vardi algorithm{{cite journal|last1=Shepp|first1=L.|last2=Vardi|first2=Y.|title=Maximum likelihood reconstruction for emission tomography|journal=IEEE Transactions on Medical Imaging|date=1982|volume=1|issue=2|pages=113–122|doi=10.1109/TMI.1982.4307558|pmid=18238264}} in the context of low-count, time-of-flight emission tomography. It was during this period that Miller met Lawrence (Larry) Shepp, and he subsequently visited Shepp several times at Bell Labs

to speak as part of the Henry Landau seminar series.

During the mid 1990s, Miller joined the Pattern Theory group at Brown University and worked with Ulf Grenander on problems in image analysis within the Bayesian framework of Markov random fields.

They established 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.

{{cite journal|last1=Grenander|first1=U.|last2=Miller|first2=M.I.|title=Representations of Knowledge in Complex Systems|journal=Journal of the Royal Statistical Society, Series B|date=1994|volume=56|issue=4|pages=549–603|jstor=2346184|doi=10.1111/j.2517-6161.1994.tb02000.x}}

These were an early 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.{{Cite journal

|author1=S. Geman |author2=D. Geman | title = Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images

| journal = IEEE Transactions on Pattern Analysis and Machine Intelligence

| volume = 6

| pages = 721–741

| year = 1984

| doi = 10.1109/TPAMI.1984.4767596

|pmid=22499653 | issue = 6

|s2cid=5837272 }}

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,{{Cite journal |editor= Walter Freiberger |title = Current and Future Challenges in the Applications of Mathematics |journal=Quarterly of Applied Mathematics }} and in a subsequent publication.{{cite journal|last1=Grenander|first1=Ulf|last2=Miller|first2=M.I.|title=Computational Anatomy: An Emerging Discipline|journal=Quarterly of Applied Mathematics|date=December 1998|volume=LVI|issue=4|pages=617–694|url=http://www.dam.brown.edu/people/mariom/AM282-01/PAPERS/LANDMARK/grenander_miller_98.pdf|doi=10.1090/qam/1668732|doi-access=free}}

In the same year with Paul Dupuis, they established the necessary Sobolev smoothness conditions requiring vector fields to have strictly greater than 2.5 square-integrable, generalized derivatives (in the space of 3-dimensions) to ensure that smooth submanifold shapes are carried smoothly via integration of the flows.{{cite journal|last1=Dupuis|first1=P.|last2=Grenander|first2=U.|last3=Miller|first3=M.I.|title=Variational Problems on Flows of Diffeomorphisms for Image Matching|journal=Quarterly of Applied Mathematics|date=September 1998|volume=56|issue=3|pages=587–600|jstor=43638248|doi=10.1090/qam/1632326|doi-access=free}} The Computational anatomy framework via diffeomorphisms at the 1mm morphological scale is one of the de facto standards for cross-section analyses of populations. Codes now exist for diffeomorphic template or atlas mapping, including

ANTS,{{Cite web|title = stnava/ANTs|url = https://github.com/stnava/ANTs/blob/master/Scripts/antsIntroduction.sh|website = GitHub|access-date = 2015-12-11}} DARTEL,{{Cite journal|title = A fast diffeomorphic image registration algorithm |journal = NeuroImage|date = 2007-10-15|pmid = 17761438|pages = 95–113|volume = 38|issue = 1|doi = 10.1016/j.neuroimage.2007.07.007|first = John|last = Ashburner|s2cid = 545830}} DEMONS,{{Cite web|title = Software - Tom Vercauteren|url = https://sites.google.com/site/tomvercauteren/software|website = sites.google.com|access-date = 2015-12-11}} LDDMM,{{Cite web|title = NITRC: LDDMM: Tool/Resource Info|url = https://www.nitrc.org/projects/lddmm-volume/|website = www.nitrc.org|access-date = 2015-12-11}} StationaryLDDMM,{{Cite web|title = Publication:Comparing algorithms for diffeomorphic registration: Stationary LDDMM and Diffeomorphic Demons|url = https://www.openaire.eu/search/publication?articleId=dedup_wf_001::ea7b28db1d4570e248acdffb6211d98d|website = www.openaire.eu|access-date = 2015-12-11|archive-url = https://web.archive.org/web/20160216022906/https://www.openaire.eu/search/publication?articleId=dedup_wf_001::ea7b28db1d4570e248acdffb6211d98d|archive-date = 2016-02-16|url-status = dead}} all actively used codes for constructing correspondences between coordinate systems based on sparse features and dense images.

David Mumford appreciated the smoothness results on existence of flows, and encouraged collaboration between Miller and the École normale supérieure de Cachan

group that 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 ongoing collaboration on shape between Miller, Alain Trouve and Laurent Younes.{{Cite web|url=http://cmla.ens-paris-saclay.fr/version-anglaise/|title=CMLA - CMLA Research Center for Applied Maths|last=Doucet|first=Sandra|website=cmla.ens-paris-saclay.fr|language=en|access-date=2017-12-06}}

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 appeared in 2002,{{cite journal|last1=Miller|first1=M.I.|last2=Trouve|first2=A.|last3=Younes|first3=L.|title=On the Metrics and Euler-Lagrange Equations of Computational Anatomy|journal=Annual Review of Biomedical Engineering|date=2002|volume=4|pages=375–405|doi=10.1146/annurev.bioeng.4.092101.125733|pmid=12117763|citeseerx=10.1.1.157.6533}}

the conservation of momentum law for shape momentum appeared in 2006,{{cite journal|last1=Miller|first1=M.I.|last2=Trouve|first2=A.|last3=Younes|first3=L.|title=Geodesic shooting for computational anatomy|journal=International Journal of Computer Vision|volume=24|issue=2|pages=209–228|doi=10.1007/s10851-005-3624-0|date=31 January 2006|pmid=20613972|pmc=2897162|bibcode=2006JMIV...24..209M }} and the summary of Hamiltonian formalism appeared in 2015.{{cite journal|last1=Miller|first1=M.I.|last2=Trouve|first2=A.|last3=Younes|first3=L.|title=Hamiltonian Systems and Optimal Control in Computational Anatomy: 100 Years Since D'Arcy Thompson|journal=Annual Review of Biomedical Engineering|date=December 2015|volume=17|pages=447–509|doi=10.1146/annurev-bioeng-071114-040601|pmid=26643025}}

Miller and John Csernansky 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 diffeomorphometry technologies.{{cite journal|last1=Csernansky|first1=J.G.|last2=Wang|first2=L.|last3=Swank|first3=J.|last4=Miller|first4=JP|last5=Gado|first5=M.|last6=McKeel|first6=D.|last7=Miller|first7=M.I.|last8=Morris|first8=J.C.|title=Preclinical detection of Alzheimer's disease: hippocampal shape and volume predict dementia onset in the elderly.|journal=NeuroImage|date=15 April 2005|volume=25|issue=3|pages=783–792|doi=10.1016/j.neuroimage.2004.12.036|pmid=15808979|s2cid=207164390}}

This was one of the papers that contributed to a deeper understanding of the disorder in its earlier stages and the recommendations of the working group to revise the diagnostic criteria for Alzheimer’s disease dementia for the first time in 27 years.{{cite web|title=Alzheimer's Diagnostic Guidelines|url=https://www.nia.nih.gov/research/dn/alzheimers-diagnostic-guidelines|publisher=Division of Neuroscience}}

In 2009, the Johns Hopkins University BIOCARD{{cite web|last1=Albert|first1=M. S.|title=BIOCARD: Predictors of Cognitive Decline Among Normal Individuals|url=http://www.alzresearch.org/biocard.cfm|website=Alzheimer's Disease Research Center|publisher=Johns Hopkins University School of Medicine}} project was initiated, led by Marilyn Albert, to study preclinical Alzheimer's disease. In 2014, Miller and Younes demonstrated that the original Braak staging of the earliest change associated to the entorhinal cortex in the medial temporal lobe could be demonstrated via diffeomorphometry methods in the population of clinical MRIs,{{cite journal|last1=Miller|first1=M.I.|last2=Younes|first2=L.|last3=Ratnanather|first3=J.T.|last4=Brown|first4=T.|last5=Trinh|first5=H.|last6=Postal|first6=E.|last7=Lee|first7=D.S.|last8=Wang|first8=M.C|last9=Mori|first9=S.|last10=Obrien|first10=R.|last11=Albert|first11=M.|title=The diffeomorphometry of temporal lobe structures in preclinical Alzheimer's disease|journal=NeuroImage: Clinical|date= 16 September 2013|volume=3|issue=352–360|doi=10.1016/j.nicl.2013.09.001|pmid=24363990|pmc=3863771|pages=352–360}} and subsequently that this could be measured via MRI in clinical populations upwards of 10 years before clinical symptoms appeared.{{cite journal|last1=Younes|first1=L.|last2=Albert|first2=M.|last3=Miller|title=Inferring changepoint times of medial temporal lobe morphometric change in preclinical Alzheimer's disease|journal=NeuroImage: Clinical|date=21 April 2014|volume=5|pages=178–187|pmid=25101236|doi=10.1016/j.nicl.2014.04.009|pmc=4110355}}

• {{cite book|author=Snyder, Donald L.|author2=Miller, Michael I.|title=Random Point Processes in Time and Space|year=1991|publisher=Springer|isbn=978-0199297061}}
• {{cite book|author=Grenander, Ulf|author2=Miller, Michael|title=Pattern Theory: From Representation to Inference|year=2007|publisher=Oxford University Press|isbn=978-0199297061}}

{{Reflist|2}}

• [http://www.cis.jhu.edu/faculty/cvs/CV_Miller_2017-01-17.pdf] Miller's Curriculum Vitae
• [https://www.orau.org/council/archive/2016/files/bios/michael-miller-bio.pdf] Miller's Short Biography
• [http://www.cis.jhu.edu/] Center for Imaging Science Website

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{{DEFAULTSORT:Miller, Michael I}}

Category:Living people

Category:Stony Brook University alumni

Category:Johns Hopkins University Department of Biomedical Engineering faculty

Category:American biomedical engineers

Category:American bioinformaticians

Category:Fellows of the American Institute for Medical and Biological Engineering

Category:Fellows of the Biomedical Engineering Society

Category:1955 births

Category:Whiting School of Engineering alumni

Category:Washington University in St. Louis fellows

Category:Washington University in St. Louis faculty

Category:Brown University faculty