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

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

Flow Characteristics of Barium Thickened Liquids during Swallowing in Healthy Adults.

Dysphagia·2026
Same author

Medical application of deep-learning-based head pose estimation from RGB image sequence.

Computers in biology and medicine·2025
Same author

Correction to: Classification of cervical vertebral maturation stages with machine learning models: leveraging datasets with high inter- and intra-observer agreement.

Progress in orthodontics·2025
Same author

Classification of cervical vertebral maturation stages with machine learning models: leveraging datasets with high inter- and intra-observer agreement.

Progress in orthodontics·2024
Same author

Factors Influencing Telehealth Service Use and Health Outcomes in Patients Undergoing Continuous Ambulatory Peritoneal Dialysis: Cross-Sectional Study.

Journal of medical Internet research·2023
Same author

Encoder-decoder network with RMP for tongue segmentation.

Medical & biological engineering & computing·2023
Same journal

A novel SE-ResNet architecture for continuous estimation of wrist and hand movements from HD-sEMG.

Medical & biological engineering & computing·2026
Same journal

Anti-aliasing-enhanced WaveUNet for clinically reliable 12-lead ECG reconstruction from limited 3-lead input.

Medical & biological engineering & computing·2026
Same journal

Deep multi-modal features based spatio-temporal video regression for non-invasive hemoglobin estimation.

Medical & biological engineering & computing·2026
Same journal

Reduced mechanical strength correlates with decreased elastin content in aortic intima-media tissue: association with dissection in human ascending aortas.

Medical & biological engineering & computing·2026
Same journal

How plaque morphology and stenosis severity govern stent-artery interaction and deployment outcomes: a computational study.

Medical & biological engineering & computing·2026
Same journal

Investigating a relation between amyloid beta plaque burden and accumulated neurotoxicity caused by amyloid beta oligomers.

Medical & biological engineering & computing·2026
查看所有相关文章

相关实验视频

Updated: Jul 2, 2025

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application
05:56

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Published on: April 14, 2023

2.5K

深度Upscale U-Net用于自动舌头细分.

Worapan Kusakunniran1, Thanandon Imaromkul2, Sophon Mongkolluksamee3

  • 1Faculty of Information and Communication Technology, Mahidol University, 999 Phuttamonthon 4 Road, Salaya, 73170, Nakhon Pathom, Thailand. worapan.kun@mahidol.edu.

Medical & biological engineering & computing
|February 19, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了深度高级U-Net (DU-UNET),用于精确的舌头细分,这对于诊断口腔癌至关重要. 通过减少功能损失,DU-UNET在U-Net上进行了改进,在现实世界的舌头图像分析中实现了高精度.

关键词:
深度UPSCALEU-NET是一个深度UPSCALEU-NET.深度学习是一种深度学习.编码器解码器编码器舌头细分的细分方式

更多相关视频

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

2.8K
Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

401

相关实验视频

Last Updated: Jul 2, 2025

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application
05:56

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Published on: April 14, 2023

2.5K
Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

2.8K
Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

401

科学领域:

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

背景情况:

  • 准确的舌头运动分析对于诊断口腔和口腔癌至关重要.
  • 自动舌头细分是测量舌头运动的先决条件.
  • 现有的U-Net模型在更深层的网络层中可能会出现功能损失.

研究的目的:

  • 提出一个改进的U-Net架构,称为Deep Upscale U-Net (DU-UNET),用于增强语言细分.
  • 为了应对细分网络中深层卷积层中特征损失的挑战.
  • 开发一个强大的舌头细分模型,适用于现实世界,远程成像场景.

主要方法:

  • 实现了一个新的深度UpscaleU-Net (DU-UNET) 架构.
  • 包括从收缩路径到膨胀路径的上层特征地图的额外上方采样.
  • 在公开可用的数据集和自己收集的五种姿势的舌头图像数据集上训练了DU-UNET模型.

主要成果:

  • 与现有方法相比,DU-UNET模型取得了更高的性能.
  • 实现了99.2%的准确性.
  • 获得了97.8%的平均交叉与联盟 (IoU),96.8%的子得分和96.8%的Jaccard得分.

结论:

  • 在深层卷积层中,DU-UNET有效地克服了功能丢失问题.
  • 拟议的模型在现实条件下对舌头细分具有高准确性和稳定性.
  • 在口腔癌检测方面,DU-UNET显示了改善诊断工具的巨大潜力.