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

Continuous glucose monitoring for prediabetes classification in a large real-world cohort: Comparison with HbA1c and fasting plasma glucose.

Diabetes research and clinical practice·2026
Same author

A new species of <i>Laophontella</i> Thompson IC & Scott A, 1903 (Copepoda, Harpacticoida, Tetragonicipitidae) from Korea, with notes on copepodid V stage.

ZooKeys·2026
Same author

Full-spectrum EEM end-member unmixing with statistical validation: A deep learning framework for organic pollution source apportionment in complex watersheds.

Journal of environmental management·2026
Same author

Corrigendum to "Evaluating alternative protocols for preventing cisplatin-induced acute kidney injury during hyperthermic intraperitoneal chemotherapy in ovarian cancer" [Volume 208, May 2026, Pages 85-90].

Gynecologic oncology·2026
Same author

Flexible laser-induced graphene biosensor enables real-time, in vivo profiling of wound healing cytokine dynamics.

Journal of nanobiotechnology·2026
Same author

Cryo-EM structure of the LARS1:IARS1 complex reveals a nutrient-responsive switch controlling mTORC1 signaling.

Nature communications·2026
Same journal

Novel Parent Survey Measures Sensory Behaviors Incorporating Sensory Modality and Stimulus Intensity.

Heliyon·2026
Same journal

Expression of concern: "SQSTM1/p62 promotes the progression of gastric cancer through epithelial-mesenchymal transition" [Heliyon 10 (2024) e24409].

Heliyon·2026
Same journal

Expression of concern: "TL1A promotes metastasis and EMT process of colorectal cancer" [Heliyon 10 (2024) e24392].

Heliyon·2026
Same journal

Expression of concern: "Factors affecting timing of surgery following neoadjuvant chemoradiation for esophageal cancer" [Heliyon 9 (2023) e23212].

Heliyon·2026
Same journal

Expression of concern: "On stratified single-valued soft topogenous structures" [Heliyon 10 (2024) e27926].

Heliyon·2026
Same journal

Expression of concern: "Artifact removal and motor imagery classification in EEG using advanced algorithms and modified DNN" [Heliyon 10 (2024) e27198].

Heliyon·2026
查看所有相关文章

相关实验视频

Updated: Jul 19, 2025

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning
08:58

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning

Published on: November 19, 2018

12.5K

基于深度学习的无标签血液学分析框架,使用光学衍射断层扫描.

Dongmin Ryu1, Taeyoung Bak2, Daewoong Ahn1

  • 1Tomocube Inc., Daejeon, 34109, Republic of Korea.

Heliyon
|August 14, 2023
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的无标签血液学分析框架,使用光学衍射断层扫描和深度学习. 该方法精确检测和分类血细胞,为传统染色方法提供更快,更具成本效益的替代方案.

关键词:
深度学习是一种深度学习.血液学分析 血液学分析没有标签的成像.对象检测检测对象检测对象检测光学衍射断层扫描仪的光学衍射断层扫描仪

更多相关视频

Label-Free Non-Linear Optics for the Study of Tubulin-Dependent Defects in Central Myelin
08:07

Label-Free Non-Linear Optics for the Study of Tubulin-Dependent Defects in Central Myelin

Published on: March 24, 2023

1.9K
Automated Quantification of Hematopoietic Cell &#8211; 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

相关实验视频

Last Updated: Jul 19, 2025

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning
08:58

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning

Published on: November 19, 2018

12.5K
Label-Free Non-Linear Optics for the Study of Tubulin-Dependent Defects in Central Myelin
08:07

Label-Free Non-Linear Optics for the Study of Tubulin-Dependent Defects in Central Myelin

Published on: March 24, 2023

1.9K
Automated Quantification of Hematopoietic Cell &#8211; 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

科学领域:

  • 生物医学工程 生物医学工程
  • 计算生物学 计算生物学
  • 医学诊断 医学诊断 医学诊断

背景情况:

  • 传统的血液学分析依赖于耗时和劳动密集的化学染色过程.
  • 无标签成像为血液学分析提供了具有成本效益和效率的替代方案.

研究的目的:

  • 开发一个无标签的血液学分析框架,使用光学衍射断层扫描和深度学习.
  • 精确检测和分类各种血细胞类型,无需化学染色.

主要方法:

  • 利用光学衍射断层扫描进行无标签的血液细胞成像.
  • 采用全卷积一阶段物体探测器 (FCOS),一个深度学习模型,用于细胞检测和分类.
  • 检测到的细胞被分为四组:红细胞,异常红细胞,血小板和白细胞.

主要成果:

  • 对象检测模型实现了0.977的血液细胞检测的平均平均精度 (mAP).
  • 在四类血细胞分类中实现了高精度,加权F1得分为0.9708,总精度为0.9712.
  • 证明了与参考设备的平均体细胞体积 (MCV) (0.905) 和平均体细胞血红蛋白 (MCH) (0.889) 的合理相关性.

结论:

  • 拟议的框架成功地证明了使用光学衍射断层扫描仪检测和分类血细胞的无标签检测和分类.
  • 这种方法为传统的血液学分析提供了一个有希望的,高效和成本效益的替代方案.
  • 这项研究证实了将先进的成像和深度学习整合到改进的诊断工具中的潜力.