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関連する概念動画

Skewness01:06

Skewness

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The measures of central tendency calculated from a data set may not reveal much about its intrinsic distribution. If a plot is made of the data set’s values, the mean and the median may not only differ, but also the plot may have more values on one side of the central tendencies. Such a data set is said to be skewed towards that side.
The longer the tail of the plot on one side, the more skewed it is. The skewness of a data set’s values suggests that the measures of central tendency...
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Orthogonal Trajectories01:26

Orthogonal Trajectories

74
Orthogonal trajectories describe the geometric relationship between two families of curves that intersect each other at right angles. One illustrative case involves a family of parabolas that open sideways along the x-axis. These curves share a common shape but differ by a scaling parameter, resulting in a set of curves that all pass through the origin and widen at different rates.Determining Orthogonal TrajectoriesTo identify the orthogonal trajectories for these parabolas, the first step...
74
Types of Skewness01:09

Types of Skewness

18.7K
If the frequency distribution of a data set is more inclined towards smaller or larger values, the distribution is said to be skewed. If data values are skewed to the right, then the distribution is called positively skewed. Conversely, if the plot is skewed to the left, the distribution is called negatively skewed.
For instance, in the middle of a pandemic, the geographical distribution of vaccine coverage may be positively skewed towards populations in the global north countries. However,...
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Diffusion01:12

Diffusion

222.3K
Diffusion is the passive movement of substances down their concentration gradients—requiring no expenditure of cellular energy. Substances, such as molecules or ions, diffuse from an area of high concentration to an area of low concentration in the cytosol or across membranes. Eventually, the concentration will even out, with the substance moving randomly but causing no net change in concentration. Such a state is called dynamic equilibrium, which is essential for maintaining overall...
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Diffusion01:21

Diffusion

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Diffusion is a type of passive transport. In passive transport, a substance tends to move from an area of high concentration to an area of low concentration until the concentration is equal across the space. For example, take the diffusion of substances through the air. When someone opens a perfume bottle in a room filled with people, the perfume is at its highest concentration in the bottle and is at its lowest at the edges of the room. The perfume vapor will diffuse, or spread away, from the...
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Constraints and Statical Determinacy01:26

Constraints and Statical Determinacy

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In structural engineering, the equilibrium of a system is not only determined by its equations of equilibrium but also with the help of constraints. Constraints refer to restrictions on the motion of a system. The proper combinations of constraints can minimize the total number of constraints needed to maintain a system in mechanical equilibrium. When this happens, the system is said to be statically determinate. For such systems, the unknown reaction supports can be estimated using equilibrium...
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Trajectory Data Analyses for Pedestrian Space-time Activity Study
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ポジティビティの制約を持つQ空間軌道のイメージングを用いた拡散歪みイメージング.

Jun Li1, Zan Chen2, Zhaoyi Teng1

  • 1Zhejiang University of Technology, Xihu District, Hangzhou City,Zhejiang Province, ChinaHangzhou City, Hangzhou, Zhejiang, 310014, China.

Physics in medicine and biology
|February 13, 2026
PubMed
まとめ

この研究では,拡散MRI分析を改善するために,Skewness Tensor Constraints (QTI-STC) でQ空間軌道のイメージングを導入しています. この新しい方法は,より高いレベルの拡散情報を組み込み,従来の技術よりも性能が優れているため,精度と信頼性を高めています.

キーワード:
Q空間軌道のイメージングディフュージョン磁気共鳴画像処理半決まったプログラミングです.歪みテンソール

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Advanced Diffusion Imaging in The Hippocampus of Rats with Mild Traumatic Brain Injury
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Advanced Diffusion Imaging in The Hippocampus of Rats with Mild Traumatic Brain Injury

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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

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関連する実験動画

Last Updated: Feb 15, 2026

Trajectory Data Analyses for Pedestrian Space-time Activity Study
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Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

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Advanced Diffusion Imaging in The Hippocampus of Rats with Mild Traumatic Brain Injury
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Advanced Diffusion Imaging in The Hippocampus of Rats with Mild Traumatic Brain Injury

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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

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科学分野:

  • メディカルイマージング (医学イメージング)
  • バイオフィジックス 生物物理学
  • 計算神経科学とは

背景:

  • 拡散MRI (dMRI) は,水拡散による組織微細構造を特徴付けます.
  • 従来のQ空間軌道のイメージング (QTI) は低次元の瞬間を使用し,斜率テンソールなどの高次元の情報を潜在的に省略します.
  • この省略は,不完全な拡散非対称性表現と推定バイアスにつながる可能性があります.

研究 の 目的:

  • 先進的なdMRI方法を開発するために,Q空間軌道のイメージングをSkewness Tensor Constraints (QTI-STC) で行う.
  • dMRI分析に,より高次の斜率テンソールとポジティビティ制約を組み込む.
  • 拡張された拡散成分分析のための新しいフィルタリング技術 (LFとQF) を導入する.

主な方法:

  • 提案されたQ空間軌道のイメージングは,Skewness Tensor Constraints (QTI-STC) を使用しています.
  • ポジティビティの制約下で,高次の斜率テンソルを組み込みました.
  • 線形線形加重 (LF) と二次線形加重 (QF) フィルターが導入されました.

主要な成果:

  • QTI-STCは,上位階の非対称性を考慮することによって,推定バイアスを軽減します.
  • LFおよびQFフィルターは,高拡散信号を強化し,低拡散信号を抑制します.
  • 実験では,QTI-STCの試算結果が,合成データにおける基本的真実に近いことを示した.

結論:

  • QTI-STCは,dMRIでより正確で完全な拡散非対称性情報を提供します.
  • 提案された方法は,騒々しいイメージング条件下でも優れた強度を示しています.
  • この進歩は,dMRIを用いた組織微細構造の改善された特徴付けを提供します.