Jove
Visualize
联系我们

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

Comparative in vitro evaluation of fourth-generation anti-GPC3 CAR T-cells in hepatocellular carcinoma.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie·2026
Same author

Macroscopic and microscopic features indicating serosal invasion of colonic adenocarcinoma.

Annals of diagnostic pathology·2026
Same author

Remote monitoring of wide-ranging real-world changes in adults following ADHD medication initiation.

Translational psychiatry·2025
Same author

Lymphomatoid Papulosis Type E With T-Cell Receptor Gamma Positivity.

Clinical, cosmetic and investigational dermatology·2025
Same author

Completion Rates of Smart Technology Ecological Momentary Assessment (EMA) in Populations With a Higher Likelihood of Cognitive Impairment: A Systematic Review and Meta-Analysis.

Assessment·2025
Same author

A novel genetic variant associated with progressive familial intrahepatic cholestasis type 3: A case series.

JPGN reports·2024
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

相关实验视频

Updated: Jun 19, 2025

Author Spotlight: Enhancing PSC-to-Functional Cell Differentiation Using ML Models Based on Live-Cell Bright-Field Imaging
11:38

Author Spotlight: Enhancing PSC-to-Functional Cell Differentiation Using ML Models Based on Live-Cell Bright-Field Imaging

Published on: October 4, 2024

532

伪细胞:基于深度学习的中枢细胞细胞检测的伪标签作为硬负采矿.

Narongrid Seesawad1, Piyalitt Ittichaiwong2, Thapanun Sudhawiyangkul1

  • 1Bio-inspired Robotics and Neural Engineering (BRAIN) Lab, School of Information Science and Technology (IST)Vidyasirimedhi Institute of Science & Technology (VISTEC) Rayong 21210 Thailand.

IEEE open journal of engineering in medicine and biology
|July 25, 2024
PubMed
概括

伪细胞在整个幻灯片图像 (WSI) 中自动检测细胞中心细胞,减少病理学家的工作量. 这种深度学习框架消除了对卵泡淋巴瘤分类标签的手动改进的需要.

关键词:
中心细胞细胞检测检测深度卷积神经网络是一个深度卷积神经网络.毛囊性淋巴瘤是一种毛囊性淋巴瘤硬负面采矿 硬负面采矿形态特征 形态特征 形态特征

更多相关视频

Automated Quantification of Hematopoietic Cell – Stromal Cell Interactions in Histological Images of Undecalcified Bone
09:31

Automated Quantification of Hematopoietic Cell – Stromal Cell Interactions in Histological Images of Undecalcified Bone

Published on: April 8, 2015

11.6K
Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures
07:05

Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures

Published on: February 15, 2022

2.6K

相关实验视频

Last Updated: Jun 19, 2025

Author Spotlight: Enhancing PSC-to-Functional Cell Differentiation Using ML Models Based on Live-Cell Bright-Field Imaging
11:38

Author Spotlight: Enhancing PSC-to-Functional Cell Differentiation Using ML Models Based on Live-Cell Bright-Field Imaging

Published on: October 4, 2024

532
Automated Quantification of Hematopoietic Cell – Stromal Cell Interactions in Histological Images of Undecalcified Bone
09:31

Automated Quantification of Hematopoietic Cell – Stromal Cell Interactions in Histological Images of Undecalcified Bone

Published on: April 8, 2015

11.6K
Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures
07:05

Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures

Published on: February 15, 2022

2.6K

科学领域:

  • 数字病理学数字病理学
  • 计算病理学计算病理学
  • 医学中的人工智能

背景情况:

  • 深度学习模型使用全幻灯片图像 (WSIs) 帮助卵泡淋巴瘤分类.
  • 目前的模型需要手动的中枢细胞识别和病理学家的精细标签进行优化.
  • 这一要求在诊断工作流程中构成了重大瓶.

研究的目的:

  • 介绍PseudoCell,这是一个对象检测框架,用于WSIs中自动检测心脏细胞.
  • 消除了对病理学家精制的广泛标签的需求,简化了模型优化.
  • 减少数字病理学中手动注释负担.

主要方法:

  • 采用混合方法,将病理学家提供的心脏细胞标签与伪负标签相结合.
  • 使用细胞形态学,从低样本虚假阳性预测生成伪负标签.
  • 开发一个对象检测框架,用于精确的中心爆发物识别.

主要成果:

  • 通过准确识别感兴趣的领域,PseudoCell显著降低了病理学家的工作量.
  • 该框架可以取决于信任值,在WSIs中消除58.18-99.35%的无关组织区域.
  • 展示PseudoCell在预先选中检测中心细胞细胞的效率.

结论:

  • 伪细胞提供了一种实用和高效的预选解决方案,用于在WSIs中检测心脏细胞.
  • 该框架消除了对精致病理学家标签的需求,提高了工作流程的效率.
  • 在诊断环境中为PseudoCell的临床实施提供指导.