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相关概念视频

Blood Flow01:29

Blood Flow

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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.
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Development of Blood Vessels01:07

Development of Blood Vessels

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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...
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Anatomy of Blood Vessels01:20

Anatomy of Blood Vessels

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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,...
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相关实验视频

Updated: May 3, 2026

Image-guided, Laser-based Fabrication of Vascular-derived Microfluidic Networks
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人工血管图像生成使用血管纹理地图.

Adriano Dos Reis Carvalho1, Matheus Viana da Silva1, Cesar H Comin1

  • 1Department of Computer Science, Federal University of São Carlos, São Carlos, SP, Brazil.

Computers in biology and medicine
|October 8, 2024
PubMed
概括

这项研究引入了一种用于生成具有现实的纹理的人工血管图像的新方法,大大减少了神经网络训练中需要手动注释的需求. 这种方法可以提高船舶识别任务的预训练性能.

科学领域:

  • 医疗成像医学成像
  • 计算生物学 计算生物学
  • 机器学习 机器学习

背景情况:

  • 在数字图像中识别血管的传统方法需要大量的像素智能注释.
  • 手动对整个船只树进行注释是耗时且昂贵的.
  • 现有的预训练方法通常集中在船只几何上,其外观是由一般统计或单独的生成网络建模的.

研究的目的:

  • 开发一种新的方法来生成具有现实的纹理的人造血管图像.
  • 为了减少在医疗图像分析中训练神经网络所需的手动注释工作.
  • 为了提高血液血管细分网络预训练的性能.

主要方法:

  • 手动注释小船段的边界,以创建纹理地图.
  • 使用逐块线性转换来将纹理图应用于表示容器几何形状的贝齐尔曲线.
  • 通过结合容器几何形状和提取的纹理来生成人工图像.

主要成果:

  • 在CORTEX上获得了高的子得分 (0.87分,在DRIVE上获得了0.74分),注释很少 (分别为0.03%和0.29%).
  • 性能非常接近以完整数据集注释获得的基线得分.
  • 在光显微镜和 fundus 摄影数据集上都表现出有效性.
关键词:
人工图像的人工图像血管模型 血管模型分段化 分段化 分段化 分段化纹理生成 纹理生成

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结论:

  • 提出的方法有效地解开了血管的几何和纹理.
  • 与现有方法相比,这种方法显著提高了网络预培训的性能.
  • 提供了一个具有成本效益的解决方案,用于训练精确的血管识别模型.