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相关概念视频

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models

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Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...
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Multicompartment Models: Overview01:14

Multicompartment Models: Overview

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Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
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Bernoulli's Equation for Flow Along a Streamline01:30

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Bernoulli's equation relates the energy conservation in a fluid moving along a streamline. The equation applies to incompressible and inviscid fluids under steady flow. For such a flow, Newton's second law is applied to a small fluid element, which experiences forces due to pressure differences, gravity, and velocity variations. The force balance leads to the following form of Bernoulli's equation:
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Bernoulli's Equation for Flow Normal to a Streamline01:16

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Bernoulli's equation for flow normal to a streamline explains how pressure varies across curved streamlines due to the outward centrifugal forces induced by the fluid's curvature. The pressure is higher on the inner side of the curve, near the center of curvature, and decreases outward to balance these centrifugal forces.
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Current density becomes discontinuous across an interface of materials with different electrical conductivities. The normal component of the current density is continuous across the boundary.
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To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
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In Silico Clinical Trials for Cardiovascular Disease
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大动脉差异:用于多分支大动脉表面生成的体积引导条件扩散模型.

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    此摘要是机器生成的。

    AortaDiff使用一种新的扩散框架从CT/MRI扫描中创建3D主动脉模型. 这种方法产生了光滑的,CFD兼容的网格,具有高的几何精度,改善了心血管研究和临床应用.

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    科学领域:

    • 医学成像和计算建模.
    • 心血管工程是什么心血管工程
    • 医疗保健中的人工智能

    背景情况:

    • 准确的3D大动脉重建对于临床诊断,手术规划和计算流体动力学 (CFD) 模拟至关重要.
    • 目前的方法通常需要大量的数据集和手动输入,限制了CFD分析的几何一致性.

    研究的目的:

    • 引入AortaDiff,这是一个基于扩散的框架,可以直接从医学成像卷中生成光滑的CFD兼容的3D大动脉表面.
    • 克服现有方法在数据集大小和手动干预方面的局限性.

    主要方法:

    • 一种体积引导条件扩散模型 (CDM) 从CT/MRI数据生成大动脉中心线.
    • 中线用于提取船舶轮,确保精确的边界划分.
    • 提取的轮被装入光滑,连续的3D表面,以实现CFD兼容的网格.

    主要成果:

    • AortaDiff成功地生成了光滑,几何精确的3D主动脉网格,适合CFD分析.
    • 该框架在有限的培训数据中表现出有效性,产生高准确度的重建.
    • 成功地重建了正常和病态的大动脉病例,包括动脉瘤和缩.

    结论:

    • AortaDiff提供了一个端到端的工作流程,用于生成与CFD兼容的大动脉网格,最小依赖大型标记数据集.
    • 该方法提供了高的几何准确性和适应各种大动脉条件的适应性.
    • 位置 AortaDiff作为心血管研究的实用工具,增强可视化和模拟能力.