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相关概念视频

Functional Classification of Joints01:09

Functional Classification of Joints

4.2K
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...
4.2K
Structural Classification of Joints01:20

Structural Classification of Joints

3.5K
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...
3.5K
Classification of Bones01:18

Classification of Bones

5.6K
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...
5.6K
Coordination Number and Geometry02:57

Coordination Number and Geometry

15.9K
For transition metal complexes, the coordination number determines the geometry around the central metal ion. Table 1 compares coordination numbers to molecular geometry. The most common structures of the complexes in coordination compounds are octahedral, tetrahedral, and square planar.
15.9K

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相关实验视频

Updated: Jul 15, 2025

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
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Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Published on: January 7, 2019

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使用半监督学习的几何和功能的联合皮层注册.

Jian Li1,2, Greta Tuckute3,4, Evelina Fedorenko3,4,5

  • 1A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School.

ArXiv
|September 25, 2023
PubMed
概括
此摘要是机器生成的。

这项研究介绍了JOSA,一个用于脑图像记录的新框架,它对准了皮质折叠模式和功能地图. 乔萨改善了解剖和功能对齐,为神经成像研究提供了强大的工具.

关键词:
皮层注册 皮层注册 皮层注册半监督学习 半监督学习

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Four-Dimensional CT Analysis Using Sequential 3D-3D Registration
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Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
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Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping

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相关实验视频

Last Updated: Jul 15, 2025

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
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Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

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Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
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科学领域:

  • 神经成像是一种神经成像.
  • 计算神经科学是一种神经科学.
  • 医学图像分析 医学图像分析

背景情况:

  • 基于大脑表面的图像注册对于大脑图像分析中皮质表面之间的空间对应至关重要.
  • 当前的方法通常假定几何学预测功能,导致由于各个学科的结构和功能变异性导致错位.

研究的目的:

  • 引入JOSA,一种基于学习的框架,用于对折叠模式和功能地图的联合皮质注册.
  • 开发一种方法,同时学习最佳地图,同时提高注册准确性.
  • 通过减少在推断过程中对功能数据的依赖来实现广泛的神经科学应用.

主要方法:

  • 开发了一种新的基于学习的皮质注册框架,名为JOSA.
  • 实施了一种半监督的培训策略.
  • 关节对齐的解剖折叠模式和功能地图.

主要成果:

  • 与现有方法相比,JOSA在解剖学和功能领域的注册性能显著改善.
  • 该框架成功地将折叠模式和功能地图同时对齐.
  • 半监督方法允许在不需要功能数据的情况下推断.

结论:

  • 通过整合解剖和功能对齐,JOSA在基于大脑表面的图像注册方面取得了重大进展.
  • 该框架在推断过程中无需功能数据的工作能力扩大了其在神经科学研究中的适用性.
  • 关节对齐方法解决了仅依赖于解剖几何学的方法的局限性.