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

Evolution of CTCF binding sites in the human genome.

Molecular biology and evolution·2026
Same author

Single-molecule electron transport near a charge-trapping orbital-level alignment.

Journal of physics. Condensed matter : an Institute of Physics journal·2026
Same author

Combining preoperative clinical and ultrasound radiomic features to predict the predominant component of combined hepatocellular carcinoma-cholangiocarcinoma.

BMC gastroenterology·2026
Same author

Effects of Integrative Approaches for the Management of Chemotherapy-Induced Peripheral Neuropathy in Colorectal Cancer Patients: A Systematic Review of Randomized Controlled Trials and Quasi-Experimental Studies.

Journal of pain research·2026
Same author

Effects of psychosocial interventions on cancer-related fatigue in patients with colorectal cancer: a systematic review and meta-analysis of randomised controlled trials.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer·2026
Same author

Non-ergodicity and noise-corrected diffuse speckle contrast analysis in deep tissue blood flow measurement.

Biomedical optics express·2026

相关实验视频

Updated: Jul 5, 2025

Retinal Vascular Reactivity as Assessed by Optical Coherence Tomography Angiography
07:23

Retinal Vascular Reactivity as Assessed by Optical Coherence Tomography Angiography

Published on: March 26, 2020

7.6K

使用OCT进行视网膜疾病分类的多尺度-denoising残留卷积网络.

Jinbo Peng1,2,3, Jinling Lu1,2,3,4, Junjie Zhuo1,2,3

  • 1State Key Laboratory of Digital Medical Engineering, School of Biomedical Engineering, Hainan University, Haiko 570228, China.

Sensors (Basel, Switzerland)
|January 11, 2024
PubMed
概括

一个新的深度学习网络有效地从光学连贯断层扫描 (OCT) 图像中对视网膜疾病进行分类,即使有显著的噪音. 这种多尺度消毒残留卷积网络 (MS-DRCN) 提高了黄斑病理的诊断准确性.

关键词:
卷积神经网络是一种卷积神经网络.多个尺度的化残留卷积网络.光学连贯性断层扫描 (OCT)视网膜疾病分类 视网膜疾病分类

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
Optical Coherence Tomography: Imaging Mouse Retinal Ganglion Cells In Vivo
08:17

Optical Coherence Tomography: Imaging Mouse Retinal Ganglion Cells In Vivo

Published on: September 22, 2017

19.3K

相关实验视频

Last Updated: Jul 5, 2025

Retinal Vascular Reactivity as Assessed by Optical Coherence Tomography Angiography
07:23

Retinal Vascular Reactivity as Assessed by Optical Coherence Tomography Angiography

Published on: March 26, 2020

7.6K
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
Optical Coherence Tomography: Imaging Mouse Retinal Ganglion Cells In Vivo
08:17

Optical Coherence Tomography: Imaging Mouse Retinal Ganglion Cells In Vivo

Published on: September 22, 2017

19.3K

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:

  • 黄斑病理导致明显的视力丧失.
  • 光学连贯断层扫描 (OCT) 对于诊断视网膜疾病至关重要.
  • 现有的深度学习模型在海外国家和地区的图像中扎着噪音,阻碍了准确的分类.

研究的目的:

  • 开发一个强大的深度学习模型,从OCT图像对视网膜疾病进行分类.
  • 克服传统网络在处理噪音方面的局限性.
  • 为了提高对黄斑病理的诊断准确度.

主要方法:

  • 提出了一个多尺度无声化的残余卷积网络 (MS-DRCN).
  • 包含一个软消噪区块 (SDB) 来自动设置噪声值.
  • 使用多级上下文块 (MCB) 和特征融合块 (FFB) 进行增强的特征提取和集成.

主要成果:

  • 在OCT2017和OCT-C4数据集上分别获得了96.4%和96.5%的准确性.
  • 与其他方法相比,在高斯和斑点噪声方面表现出优越的稳定性.
  • 在不同噪音条件下,其精度比ResNet提高了0.6%至2.9%.

结论:

  • 该MS-DRCN有效地从杂的OCT图像中对视网膜疾病进行分类.
  • 拟议的网络架构增强了特征提取和降噪能力.
  • 这种方法为改善基于OCT的视网膜疾病诊断提供了可靠的解决方案.