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相关概念视频

Curvilinear Motion: Rectangular Components01:23

Curvilinear Motion: Rectangular Components

625
Curvilinear motion characterizes the movement of a particle or object along a curved path, notably evident when envisioning a car navigating a winding road. If the car starts at point A, its position vector is established within a fixed frame of reference, where the ratio of the position vector to its magnitude signifies the unit vector pointing in the position vector's direction.
As the car advances, its position evolves over time. Quantifying the car's velocity involves computing the...
625
Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

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Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it...
531
Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

271
Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the...
271
Curvilinear Motion: Polar Coordinates01:27

Curvilinear Motion: Polar Coordinates

476
In polar coordinates, the motion of a particle follows a curvilinear path. The radial coordinate symbolized as 'r,' extends outward from a fixed origin to the particle, while the angular coordinate, 'θ,' measured in radians, represents the counterclockwise angle between a fixed reference line and the radial line connecting the origin to the particle.
The particle's location is described using a unit vector along the radial direction. Deriving the particle's position...
476
Relative Motion Analysis using Rotating Axes - Acceleration01:22

Relative Motion Analysis using Rotating Axes - Acceleration

394
Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame. The absolute velocity of point B is determined by adding the absolute velocity of point A, the relative velocity of point B in the rotating frame, and the effects caused by the angular velocity within the rotating frame.
Time differentiation is...
394
Planar Rigid-Body Motion01:22

Planar Rigid-Body Motion

547
Understanding the movement of a rigid body in planar motion involves recognizing that every particle within this body is traversing a path that maintains a consistent distance from a specific plane. This concept is fundamental in the study of physics and mechanical engineering, and it allows us to comprehend better how objects move in space.
Planar motion is typically divided into three distinct categories. The first is rectilinear translation, demonstrated by a subway train that moves along...
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相关实验视频

Updated: Sep 10, 2025

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy
07:43

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CoRRECT:运动校正定量R2*映射的深度展开框架

Xiaojian Xu1, Weijie Gan1, Satya V V N Kothapalli2

  • 1Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA.

Journal of mathematical imaging and vision
|August 25, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了CORRECT,一个统一的定量MRI (qMRI) 深度展开框架. 在加速MRI扫描中,CoRRECT有效地减少了运动和磁场不均质的物体,产生了高质量的R2*地图.

关键词:
深度展开渐变回忆回声图像重建反向问题运动纠正在 R2* 映射自主监督的深度学习

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Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation
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In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy
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In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy

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科学领域:

  • 医学成像
  • 生物物理
  • 人工智能

背景情况:

  • 定量核磁共振 (qMRI) 量化生物组织参数,但面临着文物方面的挑战.
  • 传统的qMRI方法分别处理运动和磁场等不均质的物体,从而限制性能.
  • 在QMRI中加速获取数据加剧了文物问题,需要先进的解决方案.

研究的目的:

  • 介绍CORRECT,一个统一的深度展开框架,用于QMRI的 reduction.
  • 开发基于模型的神经网络,集成运动和现场不均性纠正.
  • 在没有预先计算的校正参数的情况下实现高质量的qMRI加速采集.

主要方法:

  • 开发了一个名为CORRECT的统一深度展开 (DU) 框架.
  • 实现基于模型的端到端神经网络,并进行自我监督学习.
  • 网络直接从k空间数据中学习纠正运动和场的不均性.

主要成果:

  • CoRRECT成功地从加速多梯度回忆回声 (mGRE) 的MRI数据中恢复了无工件的R2*地图.
  • 该框架考虑了运动和场的不均性,而不需要预先计算的校正参数.
  • 在高度加速的收购环境中表现出强的表现.

结论:

  • CoRRECT提供了一种统一的方法来纠正QMRI中的文物,提高图像质量.
  • 深度展开的方法可以整合物理,生物物理和学习模型进行先进的QMRI.
  • 这项工作为更有效,更准确的定量核磁共振技术铺平了道路.