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Global optimization methods for full-reference and no-reference motion estimation with applications to atherosclerotic plaque motion and strain imaging.

机译：全参考和无参考运动估计的全局优化方法，并应用于动脉粥样硬化斑块运动和应变成像。

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摘要

Pixel-based motion estimation using optical flow models has been extensively researched during the last two decades. The driving force of this research field is the amount of applications that can be developed with the motion estimates. Image segmentation, compression, activity detection, object tracking, pattern recognition, and more recently non-invasive biomedical applications like strain imaging make the estimation of accurate velocity fields necessary.The majority of the research in this area is focused on improving the theoretical and numerical framework of the optical flow models. This effort has resulted in increased method complexity with an increasing number of motion parameters. The standard approach of heuristically setting the motion parameters has become a major source of estimation error.This dissertation is focused in the development of reliable motion estimation based on global parameter optimization methods. Two strategies have been developed. In full-reference optimization, the assumption is that a video training set of realistic motion simulations (or ground truth) are available. Global optimization is used to calculate the best motion parameters that can then be used on a separate set of testing videos. This approach helps provide bounds on what motion estimation methods can achieve. In no-reference optimization, the true displacement field is not available. By optimizing for the agreement between different motion estimation techniques, the no-reference approach closely approximates the best (optimal) motion parameters.The results obtained with the newly developed global no-reference optimization approach agree closely with those produced with the full-reference approach. Moreover, the no-reference approach calculates velocity fields of superior quality than published results for benchmark video sequences. Unreliable velocity estimates are identified using new confidence maps that are associated with the disagreement between methods. Thus, the no-reference global optimization method can provide reliable motion estimation without the need for realistic simulations or access to ground truth.The methods developed in this dissertation are applied to ultrasound videos of carotid artery plaques. The velocity estimates are used to analyze plaque motion and produce novel non-invasive elasticity maps that can help in the identification of vulnerable atherosclerotic plaques.
机译：在过去的二十年中，已经广泛研究了使用光流模型的基于像素的运动估计。该研究领域的驱动力是可以通过运动估计来开发的应用程序数量。图像分割，压缩，活动检测，目标跟踪，模式识别以及最近的非侵入式生物医学应用（如应变成像）使得需要估计准确的速度场。该领域的大部分研究集中在改进理论和数值上光流模型的框架。这种努力导致方法复杂性的增加以及运动参数数量的增加。启发式设置运动参数的标准方法已成为估计误差的主要来源。本文主要研究基于全局参数优化方法的可靠运动估计的发展。已经开发出两种策略。在全参考优化中，假设是可以使用一组逼真的运动模拟（或地面真实情况）视频训练。全局优化用于计算最佳运动参数，然后可以将其用于单独的一组测试视频。这种方法有助于确定运动估计方法可以实现的范围。在无参考优化中，真实位移字段不可用。通过优化不同运动估计技术之间的一致性，无参考方法可以逼近最佳（最佳）运动参数。新开发的全局无参考优化方法所获得的结果与全参考方法所产生的结果非常吻合。此外，无参考方法所计算的速度场质量要优于基准视频序列的已发布结果。使用与方法之间的分歧相关的新置信度图来识别不可靠的速度估计值。因此，无参考全局优化方法可以提供可靠的运动估计，而无需进行现实的模拟或获取地面真实性。本文开发的方法被应用于颈动脉斑块的超声视频。速度估计值用于分析斑块运动并产生新颖的非侵入性弹性图，可帮助识别易损的动脉粥样硬化斑块。

著录项

  • 作者

    Murillo Amaya, Sergio Eduardo.;

  • 作者单位

    The University of New Mexico.;

  • 授予单位 The University of New Mexico.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 215 p.
  • 总页数 215
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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