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相关概念视频

Blood Flow01:29

Blood Flow

Blood is pumped by the heart into the aorta, the largest artery in the body, and then into increasingly smaller arteries, arterioles, and capillaries. The velocity of blood flow decreases with increased cross-sectional blood vessel area. As blood returns to the heart through venules and veins, its velocity increases. The movement of blood is encouraged by smooth muscle in the vessel walls, the movement of skeletal muscle surrounding the vessels, and one-way valves that prevent backflow.
Overview of Blood Vessels01:14

Overview of Blood Vessels

The human cardiovascular system comprises five primary types of blood vessels: arteries, arterioles, veins, venules, and capillaries, each serving unique functions.
Arteries and Arterioles: Arteries are muscular and elastic vessels that primarily carry oxygenated blood from the heart to body tissues, except for the pulmonary artery, which carries deoxygenated blood. They have thick walls to withstand high pressure and contain a layer of muscle tissue, allowing them to expand or contract as...
Development of Blood Vessels01:07

Development of Blood Vessels

The development of the vascular system in a fetus is a complex and intricate process that begins as early as 15 to 16 days post-conception. This process starts outside the embryo, specifically in the mesoderm of the yolk sac, chorion, and connecting stalk. Approximately two days later, the formation of blood vessels occurs within the embryo itself.
The initial formation of this system is facilitated by the small amount of yolk present in the ovum and yolk sac. Blood vessels originate from...
Anatomy of Blood Vessels01:20

Anatomy of Blood Vessels

The vascular system, an integral part of the circulatory system, comprises various blood vessels that play crucial roles in maintaining the body's homeostasis. These blood vessels form a complex and efficient circulatory network. The three primary categories of blood vessels are the arteries, veins, and capillaries.
Arteries
Arteries circulate oxygenated blood from the heart, except the pulmonary artery, which transports deoxygenated blood to the lungs. Large arteries, such as the aorta, have...
Applications of Integration to Find Blood Flow01:27

Applications of Integration to Find Blood Flow

Blood flow through a cylindrical blood vessel can be mathematically described using the principles of laminar flow, a regime in which fluid moves smoothly in parallel layers. In this model, the velocity of the blood is not uniform across the cross-section of the vessel; rather, it varies with the radial distance from the center. The maximum velocity occurs along the central axis, decreasing progressively toward the vessel walls, where it reaches zero due to viscous drag.Approximating Blood...

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Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
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背景减去血管学与深度学习使用多空间时空血管学输入.

Donald R Cantrell1,2,3, Leon Cho4, Chaochao Zhou4

  • 1Department of Radiology, Northwestern University Feinberg School of Medicine, 737 N Michigan Ave, Suite 1600, Chicago, IL, 60611, USA. Donald.Cantrell@nm.org.

Journal of imaging informatics in medicine
|February 12, 2024
PubMed
概括

使用来自多个的时间信息的深度学习模型显著减少了数字减去血管学 (DSA) 中的运动工件. 一个3D U-Net模型在提高神经血管学图像质量方面表现出卓越的性能.

关键词:
卷积神经网络是一种卷积神经网络.数据增强数据增强数字减去血管学图.机器学习 机器学习神经血管学是一种神经血管学.有监督的学习学习.视觉变压器 视觉变压器

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科学领域:

  • 医疗成像医学成像
  • 人工智能的人工智能
  • 神经科学是一个神经科学.

背景情况:

  • 导管数字减去血管学 (DSA) 易受运动工件从图像采集过程中患者的运动.
  • 以前用于DSA图像增强的机器学习方法专注于单个2D,忽视时间信息.
  • 运动器件降低了DSA的诊断质量,阻碍了准确的血管可视化.

研究的目的:

  • 开发和评估改进的2D+t深度学习模型,以减少DSA中的运动工件.
  • 为了提高图像质量,利用血管图像时间序列的时间信息.
  • 为训练深度学习模型引入合成运动增强管道.

主要方法:

  • 收集了516张脑血管图 (8784系列) 并将它们分为"无运动"和"运动降低"子集.
  • 使用基于特征的计算机视觉算法开发了一个合成运动增强管道.
  • 在增强数据集上训练和评估2D U-Net,3D U-Net,SegResNet和UNETR模型.

主要成果:

  • 在减少运动工件方面,3D U-Net 模型显著超过了 2D U-Net 架构.
  • 与单2D U-Net.net相比,3D U-Net实现了较低的RMSE (23.14 ± 9.56) 和更高的多尺度SSIM (0.93 ± 0.05),而不是单2D U-Net.
  • 3D U-Net显示了与其他卷积式和基于变压器的模型,如SegResNet和UNETR.相比,具有竞争力的性能.

结论:

  • 整合多时间信息大大提高了对DSA的运动抗性深度学习算法的性能.
  • 开发的合成运动增强管道对于训练3D (2D+t) 深度学习架构是有效的.
  • 3D U-Net 模型显示了在神经血管学中减少运动器件的巨大潜力,从而提高了图像清晰度.