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

Methods of Medium Optimization01:28

Methods of Medium Optimization

74
Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...
74

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

Design and experimental study of a rigid-flexible coupled back rehabilitation robot.

Frontiers in bioengineering and biotechnology·2026
Same author

PH2ST: Prompt-guided hypergraph learning for spatial transcriptomics prediction in whole slide images.

Medical image analysis·2026
Same author

Porcine-derived amelogenin P148 in a layer-by-layer chitosan/hyaluronic acid coating for enhanced implant osseointegration.

Colloids and surfaces. B, Biointerfaces·2026
Same author

Polyethylene with Good Elasticity Synthesized by Anilinotropone Nickel Catalysts.

Inorganic chemistry·2026
Same author

ProGIS: Prototype-Guided Interactive Segmentation for Pathological Images.

IEEE transactions on medical imaging·2025
Same author

StaDis: Stability distance to detecting out-of-distribution data in computational pathology.

Medical image analysis·2025
Same journal

Long-term outcomes of adjuvant metronomic capecitabine in locoregionally advanced nasopharyngeal carcinoma: a randomized, controlled, multicenter, phase 3 study.

Nature cancer·2026
Same journal

Inhibition of ADSS2-mediated de novo AMP biosynthesis re-sensitizes acute myeloid leukemia to BH3 mimetics.

Nature cancer·2026
Same journal

GABA signaling activation drives glioblastoma progression in female mice through myeloid-derived suppressor cells.

Nature cancer·2026
Same journal

GABA shapes GBM immune responses in a sex-dependent manner.

Nature cancer·2026
Same journal

The future of tertiary lymphoid structures in cancer immunotherapy as biomarkers and therapeutic targets.

Nature cancer·2026
Same journal

Targeting PID1 generates oxysterols to switch macrophage cell fates for improved antitumor immunity.

Nature cancer·2026
查看所有相关文章

相关实验视频

Updated: May 6, 2026

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
09:10

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

Published on: August 5, 2021

2.2K

通过使用多实例学习,SMMILe可以在数字病理学中准确量化空间.

Zeyu Gao1,2, Anyu Mao3, Yuxing Dong3

  • 1Department of Oncology, University of Cambridge, Cambridge, UK.

Nature cancer
|November 19, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了SMMILe,这是一种新的计算病理学方法,可以在整个幻灯片图像中增强空间量化,而不会牺牲分类准确性. 在数字病理学中,SMMILe 提高了诊断预测和空间意识.

更多相关视频

Semi-Automated Planimetric Quantification of Dental Plaque Using an Intraoral Fluorescence Camera
09:34

Semi-Automated Planimetric Quantification of Dental Plaque Using an Intraoral Fluorescence Camera

Published on: January 27, 2023

2.4K
DNA-barcode-based Multiplex Immunofluorescence Imaging to Analyze FFPE Specimens from Genetically Reprogrammed Murine Melanoma
09:58

DNA-barcode-based Multiplex Immunofluorescence Imaging to Analyze FFPE Specimens from Genetically Reprogrammed Murine Melanoma

Published on: June 6, 2025

985

相关实验视频

Last Updated: May 6, 2026

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
09:10

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

Published on: August 5, 2021

2.2K
Semi-Automated Planimetric Quantification of Dental Plaque Using an Intraoral Fluorescence Camera
09:34

Semi-Automated Planimetric Quantification of Dental Plaque Using an Intraoral Fluorescence Camera

Published on: January 27, 2023

2.4K
DNA-barcode-based Multiplex Immunofluorescence Imaging to Analyze FFPE Specimens from Genetically Reprogrammed Murine Melanoma
09:58

DNA-barcode-based Multiplex Immunofluorescence Imaging to Analyze FFPE Specimens from Genetically Reprogrammed Murine Melanoma

Published on: June 6, 2025

985

科学领域:

  • 计算病理学计算病理学
  • 数字病理学数字病理学
  • 机器学习在医学中的应用

背景情况:

  • 空间量化对于计算病理学至关重要,但在多个实例学习 (MIL) 模型中经常丢失.
  • 现有的MIL方法可以预测整个幻灯片的图像标签,但缺乏空间意识,限制了临床应用.
  • 手动注释耗时,并且阻碍了病理图像分析中的可扩展性.

研究的目的:

  • 开发一种计算病理学方法,实现准确的全幻灯片图像 (WSI) 预测和卓越的空间量化.
  • 通过数学证明,实例级聚合可以提高MIL模型中的空间意识.
  • 引入和验证基于超级补丁的可测量的多实例学习 (SMMILe) 方法.

主要方法:

  • 开发了一个基于超级补丁的可测量的多实例学习 (SMMILe) 框架.
  • 在数学上证明了实例级聚合在MIL空间量化中的好处.
  • 在3,850个全幻灯片图像上对6种癌症类型和3个分类任务进行了SMMILe评估.
  • 与使用两个不同的编码器 (预训练ImageNet和病理特定) 的九种现有方法进行了基准SMMILe.

主要成果:

  • 在所有评估任务中,SMMILe与最先进的WSI分类性能相匹配或超过.
  • 该方法展示了出色的空间量化能力.
  • 无论使用什么编码器 (ImageNet或病理特定的基础模型),性能都是一致的.

结论:

  • SMMILe有效地将空间量化与高性能WSI分类集成在一起.
  • 拟议的实例级聚合方法克服了传统MIL方法的局限性.
  • SMMILe为推进计算病理学和数字诊断提供了一个强大的工具.