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

Kidney Structure01:45

Kidney Structure

69.6K
The kidneys are two large bean-shaped organs located in the upper abdomen. They filter the blood several times a day to remove toxins and rebalance water and electrolytes of the circulatory system via the renal veins. The kidneys receive blood directly from the heart via the renal arteries. These arteries enter the kidney at the hilum, the concave surface of the bean, where they branch and divide into smaller vessels and capillaries.
69.6K

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

Fluid-mediated nuclearity control in heterogeneous polyolefin catalysis.

Nature communications·2026
Same author

Layer-number-parity-dependent abnormal magnetic ordering in few-layer CrI3 on N-face AlN substrate.

Nature communications·2026
Same author

Development and validation of artificial intelligence-based model for bladder cancer immunophenotyping using whole slide images.

NPJ precision oncology·2026
Same author

Comparison of the learning curves of the osteotomy guide robot and guide plate-based robot-assisted total knee arthroplasty.

Arthroplasty (London, England)·2026
Same author

JUNB transcriptional regulation of KRT20 via ITGB1 activates PI3K/AKT signaling pathway against fibrosis-induced by renal injury.

Biology direct·2026
Same author

MM-CPI: A multimodal fusion framework for compound-protein interaction prediction.

International journal of biological macromolecules·2026

相关实验视频

Updated: Jun 28, 2025

Author Spotlight: Developing a Bedside Protocol for Kidney and Genitourinary Ultrasonography
03:19

Author Spotlight: Developing a Bedside Protocol for Kidney and Genitourinary Ultrasonography

Published on: June 21, 2024

1.1K

乌罗安吉尔 (UroAngel):基于使用深度学习的计算机断层扫描尿路图的单个功能预测系统.

Qingyuan Zheng1,2, Xinmiao Ni1,2, Rui Yang1,2

  • 1Department of Urology, Renmin Hospital of Wuhan University, 99 Zhang Zhi-Dong Road, Wuhan, 430060, Hubei, People's Republic of China.

World journal of urology
|April 16, 2024
PubMed
概括
此摘要是机器生成的。

一个新的深度学习系统UroAngel准确地预测了CT泌尿图像的阻塞性病患者的单个功能. 这种非侵入性方法为评估功能和指导治疗提供了可靠的替代方案.

关键词:
计算机断层扫描尿路图.卷积神经网络是一种卷积神经网络.深度学习是一种深度学习.淋巴细胞的过率是什么阻塞性脏病是一种阻塞性脏病.

更多相关视频

Whole-Kidney Three-Dimensional Staining with CUBIC
04:31

Whole-Kidney Three-Dimensional Staining with CUBIC

Published on: July 18, 2022

3.9K
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

2.7K

相关实验视频

Last Updated: Jun 28, 2025

Author Spotlight: Developing a Bedside Protocol for Kidney and Genitourinary Ultrasonography
03:19

Author Spotlight: Developing a Bedside Protocol for Kidney and Genitourinary Ultrasonography

Published on: June 21, 2024

1.1K
Whole-Kidney Three-Dimensional Staining with CUBIC
04:31

Whole-Kidney Three-Dimensional Staining with CUBIC

Published on: July 18, 2022

3.9K
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

2.7K

科学领域:

  • 医疗成像医学成像
  • 人工智能的人工智能
  • 腎臟病學 (nephrology) 是一種醫學專業.

背景情况:

  • 精确估计膜过率 (GFR) 对于管理阻塞性病 (ON) 至关重要.
  • 目前在ON中评估单个功能的方法可能是侵入性的或缺乏精度.
  • 需要使用非侵入性和方便的工具来预测ON患者的功能.

研究的目的:

  • 开发和验证UroAngel,这是一个深度学习系统,用于在ON患者中非侵入性预测单个功能.
  • 评估UroAngel的准确性与既定方程和专家放射科医生相比.

主要方法:

  • 从520名ON患者的计算机断层扫描尿路图像 (CTU) 和报告的回顾性收集.
  • 利用3D U-Net模型进行膜细分.
  • 采用后勤回归模型来预测功能水平,与MDRD,CKD-EPI方程以及专家放射科医生进行验证.

主要成果:

  • 3D U-Net 模型实现了精确的皮层细分 (迪斯相似系数:0.861).
  • 乌罗安吉尔在预测功能阶段方面表现出很高的表现,准确度为0.918.
  • 乌罗安吉尔在预测准确度方面表现优于MDRD,CKD-EPI方程和两名专家放射科医生.

结论:

  • 一个基于U-Net的3D自动化系统 (UroAngel) 可以从CTU图像直接预测单个功能阶段.
  • 乌罗安吉尔提供了一个准确,可靠,方便和非侵入性的方法来评估ON患者的功能.
  • 这种深度学习方法代表了阻塞性病管理的新进展.