Michael I. Miller

Affiliations: 
1985- Electrical engineering Washington University, Saint Louis, St. Louis, MO 
 1998- Biomedical Engineering Johns Hopkins University, Baltimore, MD 
Area:
Biomedical Data Science, Computational Anatomy, Brain Mapping, Neuroscience, Medical Imaging
Website:
https://www.bme.jhu.edu/people/faculty/michael-i-miller/
Google:
"Michael Ira Miller" OR "Michael I Michael"
Bio:

https://scholar.google.com/citations?user=Ui8pnoIAAAAJ&hl=en
DOI: 10.1007/978-3-642-69257-4_50

Parents

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Murray B. Sachs grad student 1983 Johns Hopkins (Neurotree)
 (The Statistical Coding of Simple Tones and Consonant-vowel Syllables in the Auditory Nerve)
Donald Lee Snyder post-doc 1985 Washington University (Computer Science Tree)

Children

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Aaron D. Lanterman grad student 1998 Washington University (E-Tree)
Dmitri Bitouk grad student 2007 Johns Hopkins
Can Ceritoglu grad student 2008 Johns Hopkins
Marc Vaillant grad student 2008 Johns Hopkins
BETA: Related publications

Publications

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Tward D, Brown T, Kageyama Y, et al. (2020) Diffeomorphic Registration With Intensity Transformation and Missing Data: Application to 3D Digital Pathology of Alzheimer's Disease. Frontiers in Neuroscience. 14: 52
Rezende TJR, Campos BM, Hsu J, et al. (2019) Test-retest reproducibility of a multi-atlas automated segmentation tool on multimodality brain MRI. Brain and Behavior. e01363
Liu CF, Padhy S, Ramachandran S, et al. (2019) Using Deep Siamese Neural Networks for Detection of Brain Asymmetries Associated with Alzheimer's Disease and Mild Cognitive Impairment. Magnetic Resonance Imaging
Otsuka Y, Chang L, Kawasaki Y, et al. (2019) A Multi-Atlas Label Fusion Tool for Neonatal Brain MRI Parcellation and Quantification. Journal of Neuroimaging : Official Journal of the American Society of Neuroimaging
Li X, Chen L, Kutten K, et al. (2019) Multi-atlas tool for automated segmentation of brain gray matter nuclei and quantification of their magnetic susceptibility. Neuroimage
Li Y, Liu P, Li Y, et al. (2018) ASL-MRICloud: An online tool for the processing of ASL MRI data. Nmr in Biomedicine. e4051
Ye C, Ma T, Wu D, et al. (2018) Atlas pre-selection strategies to enhance the efficiency and accuracy of multi-atlas brain segmentation tools. Plos One. 13: e0200294
Tang X, Luo Y, Chen Z, et al. (2018) A Fully-Automated Subcortical and Ventricular Shape Generation Pipeline Preserving Smoothness and Anatomical Topology. Frontiers in Neuroscience. 12: 321
Wu D, Ceritoglu C, Miller MI, et al. (2016) Direct estimation of patient attributes from anatomical MRI based on multi-atlas voting. Neuroimage. Clinical. 12: 570-581
Tward D, Miller M, Trouve A, et al. (2016) Parametric Surface Diffeomorphometry for Low Dimensional Embeddings of Dense Segmentations and Imagery. Ieee Transactions On Pattern Analysis and Machine Intelligence
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