Geometric and statistical methods for image analysis and control

图像分析和控制的几何和统计方法

• 批准号: RGPIN-2016-06742
• 负责人: Schmah, Tanya
• 金额: $ 1.46万
• 依托单位: University of Ottawa
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=710381
• 关键词: Geometric; statistical; methods; image; analysis

This proposal has three parts: (i) image registration and analysis; (ii) spatiotemporal modeling; and (iii) control of rotating bodies (e.g. satellites). The first two topics are closely related, and my focus is on methods applicable to medical imaging. The third topic may seem unrelated, but in fact draws on a common mathematical base of geometry and mechanics. The first subject of this proposal is geometric and statistical methods for image registration and analysis. We will develop new methods for registering, i.e. aligning, images, and describing shape deformations. These tasks are central to medical image analysis and many computer vision applications such as tracking and change detection. In the medical image domain, registration allows us to compare images from different people, or from the same person at different times, and do statistics on groups of images. Current registration methods work well for most images from healthy adults, but struggle with unusual images, including those of diseased or very young or old subjects, which are often precisely the ones of most interest. We will develop general methods that are more robust, more accurate or faster, and methods to simultaneously register images and detect abnormalities. The second subject is spatiotemporal models of longitudinal data from multiple subjects (or objects), for example medical imaging or clinical disease progression data. Spatiotemporal models take into account both the patterns of change and the rates of changes. For example, to find statistical patterns in the progression of a certain disease, it is useful to take into account the fact that the disease may progress more or less quickly in different individuals, even if they are following the same path of progression. We will develop improved models and statistical techniques, for example incorporating rates of change that vary in different spatial regions. A third subject of this proposal is the attitude control of rotating bodies via changes in the mass distribution. Just as a spinning skater can speed up by pulling her arms in, angular velocity in a general rotating “rigid” body (i.e. rigid in the absence of control forces) can be changed by changing its shape, i.e. its mass distribution. The general case is much more interesting than the skater example suggests: the angular velocity can change direction, not just amplitude. This kind of shape change can never be used to slow a rotating body down to rest, or initiate motion from rest, so it is not suitable for most control tasks. However, it may provide efficient solutions in some applications, for example in an imaging satellite, where it may suffice for a camera to point in the desired directions instantaneously, while always moving with nonzero velocity. I will study motion planning and optimal control for this problem, and also investigate a related problem in which a rigid object moves through a fluid by moving internal masses.

该建议包括三个部分：(1)图像配准和分析；(2)时空建模；(3)控制旋转物体(如卫星)。前两个主题密切相关，我的重点是适用于医学成像的方法。第三个主题可能看起来不相关，但实际上利用了几何和力学的共同数学基础。 这项建议的第一个主题是用于图像配准和分析的几何和统计方法。我们将开发新的配准方法，即对齐图像和描述形状变形。这些任务是医学图像分析和许多计算机视觉应用(如跟踪和变化检测)的核心。在医学图像领域，配准允许我们比较来自不同人的图像，或来自同一人的不同时间的图像，并对图像组进行统计。目前的配准方法对大多数来自健康成年人的图像都很有效，但难以处理不寻常的图像，包括患病或非常年轻或年老的受试者的图像，而这些图像往往正是最感兴趣的。我们将开发更健壮、更准确或更快的通用方法，以及同时配准图像和检测异常的方法。 第二个主题是来自多个对象(或对象)的纵向数据的时空模型，例如医学成像或临床疾病进展数据。时空模型同时考虑了变化的模式和变化的速度。例如，为了找到某种疾病进展的统计模式，考虑到这种疾病在不同的人身上可能或多或少进展得更快这一事实是有用的，即使他们遵循相同的进展路径。我们将开发改进的模型和统计技术，例如纳入不同空间区域不同的变化率。 这一建议的第三个主题是通过改变质量分布来控制旋转体的姿态。就像旋转的滑冰运动员可以通过拉手臂来加速一样，一般旋转的“刚性”物体(即在没有控制力的情况下是刚性的)的角速度可以通过改变其形状，即其质量分布来改变。通常的情况比滑冰运动员的例子更有趣：角速度可以改变方向，而不仅仅是幅度。这种形状变化永远不能用来将旋转的物体减慢到静止状态，或者从静止状态启动运动，所以它不适合大多数控制任务。然而，在某些应用中，它可能会提供有效的解决方案，例如在成像卫星中，它可能足以让相机瞬时指向所需的方向，同时始终以非零速度移动。我将研究这个问题的运动规划和最优控制，并研究一个相关的问题，在这个问题中，刚性物体通过移动内部质量在流体中运动。