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

High-sensitivity X-ray imaging based on cost-effective and large-size CZT epitaxial crystal.

Materials horizons·2026
Same author

Development and Internal Validation of a Machine Learning-Based Classification Model for Identifying Cognitive Frailty in Older Inpatients with Type 2 Diabetes Mellitus.

Clinical interventions in aging·2026
Same author

Two Fatty Acids From Host Plant Leaves Are Attractive to Soritia leptatina Adults.

Journal of chemical ecology·2026
Same author

Plasma proteome-metabolome signatures enable non-invasive early detection and lymph node risk stratification in breast cancer.

Molecular cancer·2026
Same author

Predicting adolescent suicidal tendency in Chinese secondary school students: a machine learning approach with XGBoost and SHAP interpretation.

BMC public health·2026
Same author

Autophagy and multimodal programmed cell death and their crosstalk in ulcerative colitis.

Tissue & cell·2026

相关实验视频

Updated: Jan 9, 2026

Novel In Vivo Micro-Computed Tomography Imaging Techniques for Assessing the Progression of Non-Alcoholic Fatty Liver Disease
08:41

Novel In Vivo Micro-Computed Tomography Imaging Techniques for Assessing the Progression of Non-Alcoholic Fatty Liver Disease

Published on: March 24, 2023

1.6K

STD-Net:用于多相肝损伤细分和表征的时空脱网络.

Shaoliang Zhu1, Mengjie Zou2, Qijun Wu1

  • 1Department of Hepatobiliary, Pancreas and Spleen Surgery, The People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical Sciences, Nanning, Guangxi Zhuang Autonomous Region, China.

NPJ digital medicine
|December 8, 2025
PubMed
概括

一个新的深度学习网络,STD-Net,通过将空间特征与时间动态分开来改善肝细胞癌 (HCC) 诊断. 这种方法提高了从医学图像中细分和表征肝癌的准确性.

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

3.3K
Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis
05:41

Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis

Published on: February 9, 2024

1.0K

相关实验视频

Last Updated: Jan 9, 2026

Novel In Vivo Micro-Computed Tomography Imaging Techniques for Assessing the Progression of Non-Alcoholic Fatty Liver Disease
08:41

Novel In Vivo Micro-Computed Tomography Imaging Techniques for Assessing the Progression of Non-Alcoholic Fatty Liver Disease

Published on: March 24, 2023

1.6K
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

3.3K
Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis
05:41

Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis

Published on: February 9, 2024

1.0K

科学领域:

  • 医疗成像医学成像
  • 人工智能的人工智能
  • 在瘤学瘤学.

背景情况:

  • 肝细胞癌 (HCC) 是癌症死亡的主要原因.
  • 通过医学成像进行准确的诊断对于HCC治疗至关重要.
  • 当前的深度学习模型往往无法在多相扫描中捕捉时间动态.

研究的目的:

  • 开发一个新的深度学习网络,STD-Net,以改善HCC诊断.
  • 在医学成像中明确地将空间特征提取与时间动态建模分开.
  • 为了提高HCC细分和表征的准确性和稳定性.

主要方法:

  • 推出了STD-Net,一个时空脱网络.
  • 使用共享重量3D编码器进行解剖学表示.
  • 使用基于变压器的时间模块进行顺序对比模式分析.

主要成果:

  • 在细分和表征方面,STD-Net的表现超过了最先进的基线.
  • 在HCC中获得了更高的子分数和更低的HD95.
  • 在小或低对比度的病变上表现出卓越的分类准确性和稳定的性能.

结论:

  • 时空脱是动态医学成像分析的一个有前途的范式.
  • STD-Net提供了一种更具临床相关性的方法来诊断HCC.
  • 该方法显示了在具有挑战性的病例中改善诊断准确性的潜力.