Michael I. Miller

Bio: 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.

Computing Large Deformation Metric Mappings via Geodesic Flows of Diffeomorphisms

Abstract: This paper examine the Euler-Lagrange equations for the solution of the large deformation diffeomorphic metric mapping problem studied in Dupuis et al. (1998) and Trouve (1995) in which two images I 0, I 1 are given and connected via the diffeomorphic change of coordinates I 0???1=I 1 where ?=?1 is the end point at t= 1 of curve ? t , t?[0, 1] satisfying .? t =v t (? t ), t? [0,1] with ?0=id. The variational problem takes the form $$\mathop {\arg {\text{m}}in}\limits_{\upsilon :\dot \phi _t = \upsilon _t \left( {\dot \phi } \right)} \left( {\int_0^1 {\left\| {\upsilon _t } \right\|} ^2 {\text{d}}t + \left\| {I_0 \circ \phi _1^{ - 1} - I_1 } \right\|_{L^2 }^2 } \right),$$ where ?v t? V is an appropriate Sobolev norm on the velocity field v t(·), and the second term enforces matching of the images with ?·?L 2 representing the squared-error norm. In this paper we derive the Euler-Lagrange equations characterizing the minimizing vector fields v t, t?[0, 1] assuming sufficient smoothness of the norm to guarantee existence of solutions in the space of diffeomorphisms. We describe the implementation of the Euler equations using semi-lagrangian method of computing particle flows and show the solutions for various examples. As well, we compute the metric distance on several anatomical configurations as measured by ?0 1?v t? V dt on the geodesic shortest paths.

Deformable templates using large deformation kinematics

Abstract: A general automatic approach is presented for accommodating local shape variation when mapping a two-dimensional (2-D) or three-dimensional (3-D) template image into alignment with a topologically similar target image. Local shape variability is accommodated by applying a vector-field transformation to the underlying material coordinate system of the template while constraining the transformation to be smooth (globally positive definite Jacobian). Smoothness is guaranteed without specifically penalizing large-magnitude deformations of small subvolumes by constraining the transformation on the basis of a Stokesian limit of the fluid-dynamical Navier-Stokes equations. This differs fundamentally from quadratic penalty methods, such as those based on linearized elasticity or thin-plate splines, in that stress restraining the motion relaxes over time allowing large-magnitude deformations. Kinematic nonlinearities are inherently necessary to maintain continuity of structures during large-magnitude deformations, and are included in all results. After initial global registration, final mappings are obtained by numerically solving a set of nonlinear partial differential equations associated with the constrained optimization problem. Automatic regridding is performed by propagating templates as the nonlinear transformations evaluated on a finite lattice become singular. Application of the method to intersubject registration of neuroanatomical structures illustrates the ability to account for local anatomical variability.

Pattern Separation in the Human Hippocampal CA3 and Dentate Gyrus

Abstract: Pattern separation, the process of transforming similar representations or memories into highly dissimilar, nonoverlapping representations, is a key component of many functions ascribed to the hippocampus. Computational models have stressed the role of the hippocampus and, in particular, the dentate gyrus and its projections into the CA3 subregion in pattern separation. We used high-resolution (1.5-millimeter isotropic voxels) functional magnetic resonance imaging to measure brain activity during incidental memory encoding. Although activity consistent with a bias toward pattern completion was observed in CA1, the subiculum, and the entorhinal and parahippocampal cortices, activity consistent with a strong bias toward pattern separation was observed in, and limited to, the CA3/dentate gyrus. These results provide compelling evidence of a key role of the human CA3/dentate gyrus in pattern separation.

Random Point Processes in Time and Space

Abstract: This senior graduate level textbook is the second revised edition of the textbook "Random Point Processes", written by D.L.Snyder and published in 1975. Its main subject area is point processes on multidimensional spaces, especially processes in two dimensions, reflecting the increase that has taken place in the use of point-process models for the description of data from which images of objects of interest are formed in a wide variety of scientific and engineering disciplines. Research done by the authors at the Biomedical Computer Laboratory at Washington University has resulted in newly developed models for position emission tomography and electron-microscopic autoradiography. All the applications are examples of nonparametric density estimation, which help provide new results concerning constrained estimation techniques. For these applications, the use of unconstrained maximum-likelihood estimation fails because the estimates are not consistent in the statistical sense; they do not converge, with increasing amounts of data, towards the quantity being estimated and regularization of the estimates is therefore considered essential. This graduate textbook on communications, signal processing and numerical mathematics is intended for the use of graduate students, researchers and practising engineers.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

Control of goal-directed and stimulus-driven attention in the brain

Abstract: We review evidence for partially segregated networks of brain areas that carry out different attentional functions. One system, which includes parts of the intraparietal cortex and superior frontal cortex, is involved in preparing and applying goal-directed (top-down) selection for stimuli and responses. This system is also modulated by the detection of stimuli. The other system, which includes the temporoparietal cortex and inferior frontal cortex, and is largely lateralized to the right hemisphere, is not involved in top-down selection. Instead, this system is specialized for the detection of behaviourally relevant stimuli, particularly when they are salient or unexpected. This ventral frontoparietal network works as a 'circuit breaker' for the dorsal system, directing attention to salient events. Both attentional systems interact during normal vision, and both are disrupted in unilateral spatial neglect.