Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Knee Joint01:23

Knee Joint

3.1K
The knee joint is the most complicated joint in the body. It consists of three articulations– two tibiofemoral and one patellofemoral. As is characteristic of synovial joints, the knee joint has a thin articular capsule that partially surrounds this joint cavity. Additionally, several ligaments, muscles, and cartilaginous structures support the movement of the knee.
A total of seven ligaments support the knee joint. The patellar ligament, which is also attached to the quadriceps femoris...
3.1K
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
Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT01:25

Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT

384
Calcium-Scoring CT ScanA calcium-scoring CT scan, also known as coronary artery calcium (CAC) scan, detects calcium deposits in the coronary arteries. This test assesses the risk of coronary artery disease (CAD), which can lead to cardiovascular events such as angina, heart failure, and sudden cardiac arrest.A calcium-scoring CT scan is generally recommended for individuals at intermediate risk of CAD without symptoms. It includes:Men aged 40-75 and women aged 50-75: Especially those with a...
384

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

MultiRetNet: A Lightweight Explainable AI Approach to Diabetic Retinopathy Grading and DME Detection Using Fundus-OCT Fusion.

Journal of imaging·2026
Same author

DiagPat: An Explainable Language Detection Model Using EEG Signals.

Sensors (Basel, Switzerland)·2026
Same author

Bridging loneliness and mobility: an integrated community-based rehabilitation model for older adults.

BMC geriatrics·2026
Same author

Arginine-Silicate-Inositol Promotes Femoral Fracture Healing in Rats.

Biological trace element research·2026
Same author

Reply to Dolu, K.O. Comment on "Topaloglu et al. Machine Learning-Driven Lung Sound Analysis: Novel Methodology for Asthma Diagnosis. <i>Adv. Respir. Med.</i> 2025, <i>93</i>, 32".

Advances in respiratory medicine·2026
Same author

Diagnostic Performance of Large Language Models in Musculoskeletal Ultrasound: A Comparative Evaluation of ChatGPT-5.1 and Gemini for Plantar Fasciitis.

Journal of imaging informatics in medicine·2026

相关实验视频

Updated: Jan 15, 2026

Anterior Cruciate Ligament Transection and Synovial Fluid Lavage in a Rodent Model to Study Joint Inflammation and Posttraumatic Osteoarthritis
06:28

Anterior Cruciate Ligament Transection and Synovial Fluid Lavage in a Rodent Model to Study Joint Inflammation and Posttraumatic Osteoarthritis

Published on: September 2, 2025

1.1K

TurkerNeXtV2:一种创新的CNN模型用于膝关节骨关节炎压力图像分类

Omer Esmez1, Gulnihal Deniz2, Furkan Bilek3

  • 1Department of Orthopedics, Elazig Fethi Sekin City Hospital, Elazig 23280, Turkey.

Diagnostics (Basel, Switzerland)
|October 16, 2025
PubMed
概括
此摘要是机器生成的。

TurkerNeXtV2是一种全新的轻型卷积神经网络 (CNN),在医学成像中以高精度和高效率实现了变压器级性能. 这种紧型号适用于实时临床应用.

关键词:
土耳其人NeXtV2生物医学图像分类的分类.深度学习是一种深度学习.骨关节炎检测检测器基于聚合关注的注意力.

更多相关视频

The Lower Body Positive Pressure Treadmill for Knee Osteoarthritis Rehabilitation
09:10

The Lower Body Positive Pressure Treadmill for Knee Osteoarthritis Rehabilitation

Published on: July 22, 2019

11.1K
Author Spotlight: Investigating Early Events and Long-Term Effects of ACL Injuries for Osteoarthritis Progression
06:27

Author Spotlight: Investigating Early Events and Long-Term Effects of ACL Injuries for Osteoarthritis Progression

Published on: September 29, 2023

1.2K

相关实验视频

Last Updated: Jan 15, 2026

Anterior Cruciate Ligament Transection and Synovial Fluid Lavage in a Rodent Model to Study Joint Inflammation and Posttraumatic Osteoarthritis
06:28

Anterior Cruciate Ligament Transection and Synovial Fluid Lavage in a Rodent Model to Study Joint Inflammation and Posttraumatic Osteoarthritis

Published on: September 2, 2025

1.1K
The Lower Body Positive Pressure Treadmill for Knee Osteoarthritis Rehabilitation
09:10

The Lower Body Positive Pressure Treadmill for Knee Osteoarthritis Rehabilitation

Published on: July 22, 2019

11.1K
Author Spotlight: Investigating Early Events and Long-Term Effects of ACL Injuries for Osteoarthritis Progression
06:27

Author Spotlight: Investigating Early Events and Long-Term Effects of ACL Injuries for Osteoarthritis Progression

Published on: September 29, 2023

1.2K

科学领域:

  • 计算机视觉 计算机视觉
  • 医疗成像医学成像
  • 人工智能的人工智能

背景情况:

  • 医疗成像应用的轻量级卷积神经网络 (CNN) 是有限的.
  • 现有的模型往往难以平衡有效性和计算效率.

研究的目的:

  • 为了介绍TurkerNeXtV2,一个紧的CNN设计用于医学成像.
  • 使用CNN的简单性和低计算成本,实现变压器级的有效性.
  • 通过新的架构块来提高模型稳定性和效率.

主要方法:

  • 开发了TurkerNeXtV2的两个新区块:基于聚合的注意力与反向瓶 (TNV2) 和混合降低采样模块.
  • 在稳定图像网-1k基准上预训练模型.
  • 微调并根据脚部压力骨关节炎 (OA) 数据集和血细胞图像数据集进行评估.
  • 使用精度,精度,回忆,F1得分和推断时间 (图像/秒) 测量性能.

主要成果:

  • 在稳定图像网-1k的预训练中实现了87.77%的验证准确性.
  • 在OA数据集上达到93.40%的准确性,精度和回忆率超过90%.
  • 在血液细胞数据集上达到98.52%的准确性.
  • 显示每张图像的平均推断时间为0.0078秒 (≈128.8图像/秒),超过了变压器基线.

结论:

  • 在医疗成像任务中,TurkerNeXtV2提供了高精度和低计算成本.
  • 基于聚合的注意力 (TNV2) 和混合下方采样有助于轻量化但有效的设计.
  • 该模型适合实时和临床部署.