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Diffusion01:12

Diffusion

217.1K
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...
217.1K
Diffusion01:21

Diffusion

6.3K
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...
6.3K
Facilitated Diffusion01:16

Facilitated Diffusion

1.2K
The plasma membrane, a critical structure in cellular biology, houses an array of transporters, or carrier proteins, interspersed within its lipid bilayer. These proteins play a crucial role in solute transport through facilitated diffusion, a form of passive diffusion that uses transporters to move the molecules across the membrane.
In this process, substrates such as organic compounds and ions interact with a transporter on one side, triggering conformational changes in proteins that enable...
1.2K
Theories of Dissolution: Diffusion Layer Model01:15

Theories of Dissolution: Diffusion Layer Model

1.7K
Dissolution, the process by which drug particles dissolve in a solvent, is explained by the diffusion layer model, a theoretical framework that simulates the absorption of oral drugs and allows us to analyze experimental data.
This process starts with a thin layer, saturated with the drug, forming at the interface between the solid and liquid. The solute then diffuses from this layer into the main solution. The Noyes-Whitney equation suggests that the rate of dissolution relies on the diffusion...
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Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion03:48

Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion

31.2K
Although gaseous molecules travel at tremendous speeds (hundreds of meters per second), they collide with other gaseous molecules and travel in many different directions before reaching the desired target. At room temperature, a gaseous molecule will experience billions of collisions per second. The mean free path is the average distance a molecule travels between collisions. The mean free path increases with decreasing pressure; in general, the mean free path for a gaseous molecule will be...
31.2K
Protein Diffusion in the Membrane01:24

Protein Diffusion in the Membrane

5.5K
Proteins show rotational as well as lateral diffusion across the membrane. The lateral diffusion of proteins was confirmed through the cell fusion experiment where mouse and human cells were fused, resulting in hybrid cells. When the human and mouse cells fused, the specific membrane proteins on human and mouse cells were marked with the red and green-fluorescent markers, respectively. Initially, the red and green fluorescence was located on the respective hemisphere of the cell. As time...
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Video Experimental Relacionado

Updated: Jan 25, 2026

Evolution of Staircase Structures in Diffusive Convection
07:28

Evolution of Staircase Structures in Diffusive Convection

Published on: September 5, 2018

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DVG-Diffusion: Modelo de Difusión Guiado por Doble Vista para Reconstrucción de TC a partir de Rayos X

Xing Xie, Jiawei Liu, Huijie Fan

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
    |January 23, 2026
    PubMed
    Resumen
    Este resumen es generado por máquina.

    Este estudio presenta un modelo de difusión guiado por doble vista (DVG-Diffusion) para reconstruir volúmenes de TC 3D a partir de radiografías 2D limitadas. El novedoso enfoque mejora la calidad y precisión de la imagen en la imagenología médica.

    Palabras clave:
    Reconstrucción de TCDifusión guiada por doble vistaImágenes médicasPocas vistasInteligencia artificial

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    Área de la Ciencia:

    • Imágenes Médicas
    • Visión por Computadora
    • Inteligencia Artificial

    Sus antecedentes:

    • La reconstrucción de volúmenes de TC 3D a partir de rayos X 2D de pocas vistas es un desafío debido a la naturaleza de proyección de los rayos X.
    • Los métodos existentes de aprendizaje profundo enfrentan dificultades en el mapeo complejo de rayos X 2D a TC 3D.

    Objetivo del estudio:

    • Desarrollar una red de aprendizaje profundo eficaz para la reconstrucción de volúmenes de TC 3D de alta fidelidad a partir de proyecciones de rayos X 2D limitadas.
    • Reducir la dificultad de aprendizaje en la reconstrucción de TC incorporando la síntesis de nuevas vistas y la alineación de características.

    Principales métodos:

    • Se propuso un modelo de difusión guiado por doble vista (DVG-Diffusion) que integra vistas de rayos X reales y sintetizadas.
    • Se utilizó un codificador guiado por parámetros de vista para la extracción de características alineadas espacialmente.
    • Se empleó un modelo de difusión latente condicionado a características de doble vista para el refinamiento de la representación latente de TC.

    Principales resultados:

    • DVG-Diffusion logró un equilibrio entre alta fidelidad y calidad perceptual en la reconstrucción de TC.
    • Los resultados experimentales demostraron un rendimiento superior en comparación con los métodos de vanguardia.
    • Se presentó un análisis exhaustivo de las vistas y la calidad de la reconstrucción.

    Conclusiones:

    • El modelo propuesto DVG-Diffusion reconstruye eficazmente volúmenes de TC 3D a partir de rayos X de pocas vistas.
    • Las estrategias de guía de doble vista y alineación de características mejoran significativamente la precisión y calidad de la reconstrucción.
    • El método ofrece una solución prometedora para los desafíos de imagenología de TC de dosis baja y vistas limitadas.