Computational anatomy and diffeomorphometry: A dynamical systems model of neuroanatomy in the soft condensed matter continuum.

IF 7.9 Q1 Medicine Wiley Interdisciplinary Reviews-Systems Biology and Medicine Pub Date : 2018-11-01 Epub Date: 2018-06-04 DOI:10.1002/wsbm.1425
Michael I Miller, Sylvain Arguillère, Daniel J Tward, Laurent Younes
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引用次数: 7

Abstract

The nonlinear systems models of computational anatomy that have emerged over the past several decades are a synthesis of three significant areas of computational science and biological modeling. First is the algebraic model of biological shape as a Riemannian orbit, a set of objects under diffeomorphic action. Second is the embedding of anatomical shapes into the soft condensed matter physics continuum via the extension of the Euler equations to geodesic, smooth flows with inverses, encoding divergence for the compressibility of atrophy and expansion of growth. Third, is making human shape and form a metrizable space via geodesic connections of coordinate systems. These three themes place our formalism into the modern data science world of personalized medicine supporting inference of high-dimensional anatomical phenotypes for studying neurodegeneration and neurodevelopment. The dynamical systems model of growth and atrophy that emerges is one which is organized in terms of forces, accelerations, velocities, and displacements, with the associated Hamiltonian momentum and the diffeomorphic flow acting as the state, and the smooth vector field the control. The forces that enter the model derive from external measurements through which the dynamical system must flow, and the internal potential energies of structures making up the soft condensed matter. We examine numerous examples on growth and atrophy. This article is categorized under: Analytical and Computational Methods > Computational Methods Laboratory Methods and Technologies > Imaging Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models.

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计算解剖学和微分形态学:软凝聚态连续体中神经解剖学的动力系统模型。
计算解剖学的非线性系统模型在过去几十年里出现,是计算科学和生物建模三个重要领域的综合。首先是生物形状作为黎曼轨道的代数模型,黎曼轨道是一组在微分同态作用下的物体。第二是将解剖形状嵌入到软凝聚态物理连续体中,通过将欧拉方程扩展到测地线,具有逆的平滑流动,为萎缩的可压缩性和增长的扩张编码散度。三是通过坐标系的测地线连接,使人的形体形成一个可度量的空间。这三个主题将我们的形式主义带入个性化医学的现代数据科学世界,支持高维解剖表型的推断,以研究神经变性和神经发育。出现的生长和萎缩的动力系统模型是由力、加速度、速度和位移组织起来的,相关的哈密顿动量和微分同态流作为状态,光滑矢量场作为控制。进入模型的力来源于动力系统必须通过的外部测量,以及构成软凝聚态物质的结构的内部势能。我们研究了许多关于生长和萎缩的例子。本文分类如下:分析与计算方法>计算方法实验室方法与技术>系统特性与过程成像模型>器官、组织和生理模型。
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CiteScore
18.40
自引率
0.00%
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0
审稿时长
>12 weeks
期刊介绍: Journal Name:Wiley Interdisciplinary Reviews-Systems Biology and Medicine Focus: Strong interdisciplinary focus Serves as an encyclopedic reference for systems biology research Conceptual Framework: Systems biology asserts the study of organisms as hierarchical systems or networks Individual biological components interact in complex ways within these systems Article Coverage: Discusses biology, methods, and models Spans systems from a few molecules to whole species Topical Coverage: Developmental Biology Physiology Biological Mechanisms Models of Systems, Properties, and Processes Laboratory Methods and Technologies Translational, Genomic, and Systems Medicine
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