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相关概念视频

Muscles of the Leg that Move the Foot and Toes01:28

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The human leg comprises an intricate system of muscles that facilitate the movement of feet and toes. Within this system, the muscles are categorized into the anterior, lateral, and posterior compartments, each with a unique set of muscles carrying out specific functions.
Anterior Compartment
The anterior compartment includes muscles that contribute to the dorsiflexion of the foot. This compartment houses the tibialis anterior, extensor hallucis longus, and extensor digitorum longus muscles....
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Pulse assessment sites are crucial in evaluating a patient's cardiovascular health. By assessing the pulsations of arteries at specific anatomical locations, healthcare professionals can gather valuable information about blood flow, heart rate, and peripheral circulation. Understanding these pulse assessment sites is essential for conducting comprehensive cardiovascular evaluations and monitoring patients' overall health. These sites are strategically chosen due to the accessibility and...
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Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
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相关实验视频

Updated: Jul 15, 2025

Predictive Measurement for Windlass Change in Length and Selected Treatment Outcomes in Chronic Plantar Fasciitis
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Predictive Measurement for Windlass Change in Length and Selected Treatment Outcomes in Chronic Plantar Fasciitis

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使用脚部压力图像进行脚类型分类的深度学习方法.

Yangyang Zhao1, Jiali Zhou1, Fei Qiu2

  • 1School of Medicine, Xiamen University, Xiamen, Fujian, China.

Frontiers in bioengineering and biotechnology
|September 28, 2023
PubMed
概括
此摘要是机器生成的。

深度学习的ResNet-50模型使用脚部压力图像准确地识别平脚类型,优于其他方法,用于更好的临床评估.

关键词:
这就是ResNet-50的特点.这就是YOLO-v55.深度学习是一种深度学习.平脚是一种平脚.脚类型识别 脚类型识别多个标签分类的分类.

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科学领域:

  • 生物力学 生物力学
  • 医疗成像医学成像
  • 人工智能的人工智能

背景情况:

  • 平脚形是一种常见的疾病,具有重大临床影响.
  • 准确识别脚类型对于有效的治疗和干预至关重要.
  • 足部压力成像为足部评估提供了有价值的工具.

研究的目的:

  • 评估深度学习模型在识别平脚类型方面的有效性.
  • 为了比较You Only Look Once v5 (YOLO-v5) 和多标签分类模型的性能.
  • 引入一种改进的深度学习方法,用于增强脚类型检测.

主要方法:

  • 研究人员使用了来自125个人的1573张脚部压力图像的数据集.
  • 您只看一次v5 (YOLO-v5) 和多标签分类模型被训练和评估.
  • 开发了一种改进的YOLO-v5模型,具有注意力机制 (SE,CBAM) 和基于ResNet-50的多标签模型.
  • 一个单独的数据集用于模型验证和比较.

主要成果:

  • 基于ResNet-50的多标签分类模型实现了最高的准确性 (0.826).
  • 使用SE和CBAM模块改进的YOLO-v5模型显示性能提高 (0.652和0.717分别).
  • 拟议的模型显著优于标准YOLO-v5和普通脚部压力系统.

结论:

  • 使用ResNet-50的基于深度学习的多标签分类在检测平脚类型方面表现出卓越的性能.
  • 这种模型有可能评估患有足部异常疾病的患者的临床康复状态.
  • 用多样化的患者数据进行进一步培训,可以将其应用扩展到各种脚病理.