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相关概念视频

Classification of Bones01:18

Classification of Bones

9.4K
The bones of the human skeletal system are of varied shapes, sizes, and functions. They can be classified based on their shape and function into four major classes: long bones, short bones, flat bones, and irregular bones. Some classifications include a fifth type, the sesamoid bones, as a separate class, whereas others categorize them under short bones.
Long and Short Bones
The appendicular skeleton, particularly the upper and lower limbs, is primarily made of long and short bones. The...
9.4K
Structural Classification of Joints01:20

Structural Classification of Joints

6.9K
Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
A fibrous joint is where the adjacent bones are united by fibrous connective...
6.9K
Functional Classification of Joints01:09

Functional Classification of Joints

6.5K
Functional Classification of Joints
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses  or amphiarthroses, whereas all synovial joints are classified as diarthroses.
Synarthrosis
An...
6.5K
Bone Remodeling01:40

Bone Remodeling

40.2K
Bone remodeling is a continuous and balanced process of bone resorption by osteoclasts and bone formation by osteoblasts. In adults, it helps maintain bone mass and calcium homeostasis. While mechanical stress can stimulate turnover as part of the normal maintenance and reparative process, several hormones also regulate bone remodeling.
40.2K
Bone Structure01:55

Bone Structure

51.4K
Within the skeletal system, the structure of a bone, or osseous tissue, can be exemplified in a long bone, like the femur, where there are two types of osseous tissue: cortical and cancellous.
51.4K
Gross Anatomy of Bone01:17

Gross Anatomy of Bone

8.7K
The two main features of a long bone are the diaphysis and the epiphysis.
The diaphysis is the tubular shaft that runs between the proximal and distal ends of the bone. The walls of the diaphysis are composed of dense and hard compact bone made of numerous osteons — the functional unit of the compact bone. The hollow region in the diaphysis is called the medullary cavity, which harbors the bone marrow. In infants and children, this marrow cavity is filled with red marrow, whereas in...
8.7K

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相关实验视频

Updated: Jan 8, 2026

Outer-Boundary Assisted Segmentation and Quantification of Trabecular Bones by an Imagej Plugin
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Outer-Boundary Assisted Segmentation and Quantification of Trabecular Bones by an Imagej Plugin

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自动化关节空间检测提高了骨段的精度.

H Mark Kenney1, Daniel Lichau2, Rémi Blanc2

  • 1Center for Musculoskeletal Research, University of Rochester Medical Center; Department of Pathology & Laboratory Medicine, University of Rochester Medical Center; Department of Medicine, University of Rochester Medical Center; howard_kenney@urmc.rochester.edu.

Journal of visualized experiments : JoVE
|December 15, 2025
PubMed
概括
此摘要是机器生成的。

深度学习模型自动化了从微型CT扫描中分析小鼠爪解剖,与以前的方法相比,大大提高了关节空间分割的准确性. 性能随着关节炎的严重程度和年龄的增加而下降.

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Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
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Longitudinal Micro-Computed Tomography Image Analysis for User-Defined Region of Interest in Critical-Sized Bone Defects
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Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
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Longitudinal Micro-Computed Tomography Image Analysis for User-Defined Region of Interest in Critical-Sized Bone Defects
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科学领域:

  • 生物医学成像技术 生物医学成像技术
  • 计算解剖学的计算解剖学
  • 深度学习应用程序

背景情况:

  • 复杂的解剖结构的手动细分是耗时的,需要专业知识,并遭受观察者之间的变化.
  • 数字图像分析,特别是深度学习 (DL),为地标检测和细分提供了自动化解决方案.
  • 以前的半自动化 (SA) 方法在详细解剖分析的准确性和效率上存在局限性.

研究的目的:

  • 开发和评估一个监督的深度学习模型,用于在小鼠爪中自动细分关节空间.
  • 将DL模型的性能与现有的SA方法进行比较.
  • 评估疾病严重程度和年龄对炎症性关节炎小鼠模型细分精度的影响.

主要方法:

  • 对小鼠后腿和前腿微型计算机断层扫描 (micro-CT) 数据集的监督自动化分析.
  • 使用3D U-Net DL架构与ResNet-18骨干进行联合空间预测.
  • 整合了结构增强,张量投票和输出扩展以改进细分.
  • 训练模型使用野生类型 (WT) 后翼标签作为基本真相,并对WT和TNF-Tg小鼠进行了测试.

主要成果:

  • 与SA方法相比,DL关节空间预测模型在健康关节中显著提高了细分精度.
  • 在TNF-Tg小鼠中,随着疾病严重程度和年龄的增加,细分精度下降.
  • 对前腿的测试也显示,在关节炎严重程度较高的情况下,准确性降低.

结论:

  • 开发的监督DL模型优于最近的SA方法,用于对小鼠爪的健康关节空间进行细分.
  • 虽然该模型的性能随着疾病进展和年龄的增长而下降,但它显示了催化结构特定细分的进一步发展的潜力.
  • 这种自动化的方法可以增强复杂的骨解剖学和疾病修饰结构的调查.