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

SERS-based detection of pesticide residues in food: substrate fabrication, optimization, and applications.

Analytical methods : advancing methods and applications·2026
Same author

Ternary classification prediction and heterogeneity quantification for HER2-Zero, -low, and -positive in breast cancer using HER2-targeted PET/CT imaging.

European journal of nuclear medicine and molecular imaging·2026
Same author

Effectiveness of Seasonal Influenza Vaccination Against Medically Attended Influenza in People With Chronic Respiratory Diseases: A Multicenter, Test-Negative, Case-control Study.

Open forum infectious diseases·2026
Same author

Molecularly Encoded Regulation of DNA Self-Assembly Crystallization in a Closed Homogeneous Solution System.

Nano letters·2026
Same author

Efficient treatment of rural domestic wastewater using glass pumice derived from waste glass in constructed wetlands: A pathway to sustainable resource valorization.

Environmental research·2025
Same author

Bidirectional Photoregulated Chromism in Pyridinium Derivatives via Secondary Excitation-Driven Electron Transfer.

Angewandte Chemie (International ed. in English)·2025

相关实验视频

Updated: Jul 29, 2025

Efficient and Consistent Generation of Retinal Pigment Epithelium/Choroid Flatmounts from Human Eyes for Histological Analysis
07:59

Efficient and Consistent Generation of Retinal Pigment Epithelium/Choroid Flatmounts from Human Eyes for Histological Analysis

Published on: October 28, 2022

2.8K

基于ResNet的Kayser Fleischer环形图像的分级方法

Wei Song1, Ling Xin1, Jiemei Wang2

  • 1The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, 230031, China.

Heliyon
|May 26, 2023
PubMed
概括

这项研究开发了一种人工智能系统,用于检测和分类威尔逊病 (WD) 患者的凯塞-弗莱舍尔 (K-F) 环. 深度学习模型,特别是ResNet34,实现了高精度,有助于早期WD诊断.

关键词:
在 HLD HLD 中.在KF中,KF是KF.这就是ResNet ResNet.威尔逊病是威尔逊病的一种疾病.这就是YOLO算法.

更多相关视频

Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.3K
Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing
06:25

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing

Published on: February 23, 2024

645

相关实验视频

Last Updated: Jul 29, 2025

Efficient and Consistent Generation of Retinal Pigment Epithelium/Choroid Flatmounts from Human Eyes for Histological Analysis
07:59

Efficient and Consistent Generation of Retinal Pigment Epithelium/Choroid Flatmounts from Human Eyes for Histological Analysis

Published on: October 28, 2022

2.8K
Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.3K
Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing
06:25

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing

Published on: February 23, 2024

645

科学领域:

  • 眼科医生 眼科 眼科
  • 医疗成像医学成像
  • 人工智能的人工智能

背景情况:

  • 凯瑟-弗莱舍尔 (K-F) 环是威尔逊病 (WD) 的关键指标.
  • 早期检测和分类K-F环对于有效的WD患者管理至关重要.
  • 目前对K-F环的诊断方法可能是主观的,耗时的.

研究的目的:

  • 开发和评估深度学习模型,用于K-F环的自动检测和分级.
  • 为WD患者创建一个全面的K-F环图像数据库.
  • 评估各种卷积神经网络 (CNN) 的性能,用于K-F环分析.

主要方法:

  • 收集并策划了一组数据集,其中包括来自399名WD患者的1850张K-F环图像.
  • 利用YOLO进行初始的角膜K-F环检测和图像细分.
  • 在KFID数据集上训练和评估深度CNN (VGG,ResNet,DenseNet) 用于K-F环分级.

主要成果:

  • ResNet34获得了最高的召回 (95.23%),特异性 (96.99%) 和F1评分 (95.23%).
  • 丹斯网显示了最好的精度 (95.66%).
  • 测试模型的整体准确度在89.88%至95.31%之间.

结论:

  • 深度学习模型,特别是ResNet,对于自动化K-F环评分是有效的.
  • 开发的系统有望提高WD诊断的准确性和效率.
  • 这种人工智能驱动的方法可以显著帮助临床医生诊断威尔逊病.