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相关概念视频

Classification of Skeletal Muscle Fibers01:48

Classification of Skeletal Muscle Fibers

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Skeletal muscles continuously produce ATP to provide the energy that enables muscle contractions. Skeletal muscle fibers can be categorized into three types based on differences in their contraction speed and how they produce ATP, as well as physical differences related to these factors. Most human muscles contain all three muscle fiber types, albeit in varying proportions.
Slow-Twitch Muscle Fibers
Slow oxidative, muscle fibers appear red due to large numbers of capillaries and high levels of...
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相关实验视频

Updated: May 23, 2025

Semi-automated Analysis of Mouse Skeletal Muscle Morphology and Fiber-type Composition
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对于深度学习的最小注释管道 骨肌肉的细分

Pierre-Yves Baudin1, Fabian Balsiger2,3, Lea Beck2,3

  • 1Institute of Myology, Neuromuscular Investigation Center, NMR Laboratory, Paris, France.

NMR in biomedicine
|May 20, 2025
PubMed
概括

这项研究提出了一种高效的代方法,用于自动骨肌肉MRI细分,显著减少手动注释. 开发的模型实现了与现有方法相比较的高质量细分,使定量MRI生物标志物的临床翻译成为可能.

关键词:
自动细分自动细分自动细分神经肌肉疾病 神经肌肉疾病在 nnU-net 中.定量的MRI是指MRI的数量.这是骨肌肉.

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科学领域:

  • 医疗成像医学成像
  • 生物医学工程 生物医学工程
  • 放射学 放射学是一门学科.

背景情况:

  • 将定量骨肌MRI生物标志物转化为临床实践需要高效的自动细分技术.
  • 尽量减少手工注释工作对于这些方法的广泛采用至关重要.

研究的目的:

  • 研究一种简单,代的方法来构建高质量的自动骨肌肉MRI细分模型.
  • 为了减少训练细分模型所需的手动注释工作.

主要方法:

  • 一个nnU-Net细分模型被训练使用70个定量MRI大腿检查的追溯数据库从健康个体和神经肌肉疾病患者.
  • 采用了一种代程序,逐步将案例添加到培训套件中,并使用五级视觉评级表来评估细分质量.
  • 在一个独立的测试集 (n=20) 上,使用子系数 (DICE),95%的豪斯多夫距离 (HD95) 和定量生物标志物 (CSA,FF,水-T1/T2) 评估了细分质量.

主要成果:

  • 与最近的工作相比,通过较小的训练集 (n=30) 实现了高质量的细分 (DICE=0.88±0.15/0.86±0.14,HD95=6.35±12.33/6.74±11.57 mm)
  • 关于细分质量的评价者间的协议是公平到中等的,在代中观察到逐渐改善模型.
  • 定量结果与手动划分的差异很小 (MAD:CSA=65.2 mm2,FF=1%,水-T1=8.4 ms,水-T2=0.35 ms),具有可比变性.

结论:

  • 提出的代方法有效地构建了高质量的自动骨肌肉MRI细分模型,减少了手动注释.
  • 该模型的性能与最先进的方法相美,促进了对骨肌肉评估的定量MRI生物标志物的临床翻译.
  • 该方法在健康和病理肌肉成像研究中展示了有效和可靠的细分潜力.