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Michael I. Miller

Researcher at Johns Hopkins University

Publications -  640
Citations -  38471

Michael I. Miller is an academic researcher from Johns Hopkins University. The author has contributed to research in topics: Large deformation diffeomorphic metric mapping & Computational anatomy. The author has an hindex of 92, co-authored 599 publications receiving 34915 citations. Previous affiliations of Michael I. Miller include University of Tennessee & Discovery Institute.

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Automated generation of sentence-based descriptors from imaging data

TL;DR: In this article, a computer-implemented method, a computer system and a non-transitory computer-readable medium for constructing human-readable sentences from imaging data of a subject can include: receiving imaging data including image elements of at least one region of interest of the subject, segmenting the image data into a plurality of sub-regions, where each sub-region includes a portion of the image elements, calculating an abnormality factor for each of the subregions by quantitatively analyzing segmented image information of the imaging data from a normal database using data from
Journal ArticleDOI

Extended-Release Memantine (28 mg, Once Daily) and Sustained Behavioral Improvement: Post Hoc Responder Analysis from a Randomized Trial in Patients with Moderate to Severe Alzheimer's Disease (P04.197)

TL;DR: In this post hoc analysis, memantine ER treatment of patients with moderate to severe AD was associated with a significantly higher rate of sustained behavioral improvement, compared with placebo.
Journal ArticleDOI

Corrigendum to “Abnormalities of cingulate gyrus neuroanatomy in schizophrenia” [Schizophrenia Research 93 (1–3) (2007) 66–78]

TL;DR: This paper presents a meta-modelling study that aims to demonstrate the efforts towards in-situ applicability of EMMARM, which aims to provide real-time information about the dynamic response of the immune system to disease.
Proceedings ArticleDOI

Change Point Estimation of the Hippocampal Volumes in Alzheimer's Disease

TL;DR: This paper proposes a novel statistical method for estimating the change point of the hippocampus, as extracted from structural magnetic resonance imaging scans, in relation to clinical symptom onset using a linear mixed-effect statistical model.