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

Glaucoma: Overview01:25

Glaucoma: Overview

1.5K
Glaucoma is an eye condition characterized by increased intraocular pressure that damages the retina and optic nerve, leading to irreversible blindness if left untreated. The human eye has various components, including the cornea, iris, pupil, lens, and optic nerve. Aqueous humor is secreted by the epithelium of the ciliary body in the posterior chamber and flows through the trabecular meshwork and canal of Schlemm, maintaining normal intraocular pressure. The trabecular meshwork and the canal...
1.5K
Open Angle Glaucoma: Treatment01:27

Open Angle Glaucoma: Treatment

1.0K
In open-angle glaucoma, the iridocorneal angle remains open, but the trabecular meshwork becomes stiff, slowing down the outflow of aqueous humor. This causes a buildup of aqueous humor in the anterior chamber, leading to a sudden increase in intraocular pressure. The treatment for open-angle glaucoma focuses on reducing the elevated intraocular pressure by either decreasing the secretion of aqueous humor or increasing its outflow.
Drugs such as carbonic anhydrase inhibitors, α2- and...
1.0K

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

Sequential Deep Learning to Predict Non-Central to Central Geographic Atrophy Progression from OCT Imaging.

medRxiv : the preprint server for health sciences·2026
Same author

Explicit Inclusion of Diabetes Mellitus Without Retinopathy Within Diabetic Retinopathy Prediction.

Translational vision science & technology·2026
Same author

Deep transfer learning for detection of placenta-mediated diseases from ultrasound images.

Scientific reports·2026
Same author

Summary of Research: Aflibercept 8 mg versus Faricimab Treat‑and‑Extend for Diabetic Macular Edema or Neovascular Age‑Related Macular Degeneration: A Bayesian Fixed‑Effect Network Meta‑analysis of Clinical Trials.

Ophthalmology and therapy·2026
Same author

Multi-OCT-SelfNet: integrating self-supervised learning with multi-source data fusion for enhanced multi-class retinal disease classification.

Frontiers in systems biology·2026
Same author

Semaglutide and Neovascular Age-Related Macular Degeneration Among Adults with Type 2 Diabetes: An OHDSI Network Study.

Ophthalmology·2026

相关实验视频

Updated: Feb 25, 2026

Multimodal Volumetric Retinal Imaging by Oblique Scanning Laser Ophthalmoscopy oSLO and Optical Coherence Tomography OCT
12:22

Multimodal Volumetric Retinal Imaging by Oblique Scanning Laser Ophthalmoscopy oSLO and Optical Coherence Tomography OCT

Published on: August 4, 2018

9.0K

联合学习多种疾病眼科诊断使用OCT血管学.

Ahammed Sakir Nabil1, Sina Gholami1, Theodore Leng2

  • 1Department of Electrical and Computer Engineering, University of North Carolina at Charlotte, Charlotte, North Carolina.

Ophthalmology science
|February 24, 2026
PubMed
概括
此摘要是机器生成的。

联合学习 (FL) 策略显示了使用OCT血管学 (OCTA) 进行多种疾病视网膜分类的前景,实现了与集中方法相比的性能,同时保持了患者的隐私.

关键词:
与年龄相关的黄斑变性 (AMD)糖尿病视网膜病变 (DR) 是一种联合学习是联合学习.光学连贯断层扫描血管学 (OCTA)保护隐私的人工智能保护人工智能

更多相关视频

Author Spotlight: Ex Vivo OCT-Based Multimodal Imaging of Human Donor Eyes for Research into Age-Related Macular Degeneration
10:14

Author Spotlight: Ex Vivo OCT-Based Multimodal Imaging of Human Donor Eyes for Research into Age-Related Macular Degeneration

Published on: May 26, 2023

4.3K
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

3.6K

相关实验视频

Last Updated: Feb 25, 2026

Multimodal Volumetric Retinal Imaging by Oblique Scanning Laser Ophthalmoscopy oSLO and Optical Coherence Tomography OCT
12:22

Multimodal Volumetric Retinal Imaging by Oblique Scanning Laser Ophthalmoscopy oSLO and Optical Coherence Tomography OCT

Published on: August 4, 2018

9.0K
Author Spotlight: Ex Vivo OCT-Based Multimodal Imaging of Human Donor Eyes for Research into Age-Related Macular Degeneration
10:14

Author Spotlight: Ex Vivo OCT-Based Multimodal Imaging of Human Donor Eyes for Research into Age-Related Macular Degeneration

Published on: May 26, 2023

4.3K
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

3.6K

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:

  • 使用OCT血管学 (OCTA) 进行视网膜疾病分类对于诊断和治疗至关重要.
  • 联合学习 (FL) 为多机构数据分析提供了一种保护隐私的方法.
  • 在优化 FL 针对异质医疗数据方面存在挑战.

研究的目的:

  • 用OCT血管学 (OCTA) 系统评估用于多种疾病视网膜分类的联合学习 (FL) 策略.
  • 在现实的异质条件下建立基础可行性并优化FL性能.
  • 确保在多机构的OCTA数据分析中保护隐私.

主要方法:

  • 一个追溯的多中心FL研究,具有2部分实验设计 (同质和异质条件).
  • 评估了五种FL聚合策略 (FedAvg,FedProx,FedMRI,FedAdagrad,FedYogi) 在各种架构,转移学习和局部时代配置中.
  • 整合和评估安全机制,如差异隐私和安全聚合.

主要成果:

  • 在简化分类方面,FL在集中培训中取得了优异的成绩 (72.09%的准确率).
  • 采用特定结策略的DenseNet121架构优化了性能 (79.55%的精度,89.68%的ROC-AUC).
  • 联合的近接显示了对异质性的弹性;安全的聚合平衡了隐私和实用性.

结论:

  • 联合学习 (FL) 为基于OCTA的多机构疾病分类提供了一个全面的,保护隐私的解决方案.
  • 优化的FL策略可以与集中式方法相匹配或超过.
  • 仔细选择架构,优化和安全机制是临床实用性和监管合规性的关键.