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

Artificial Intelligence Detection Scores in Screening Mammography for Early Breast Cancer Alerts.

Radiology·2026
Same author

Lesion detectability and masking disparity assessment in breast tomosynthesis across diverse populations using in-silico imaging trials.

IEEE transactions on medical imaging·2026
Same author

Cost-Effectiveness of Artificial Intelligence in Breast Cancer Screening: An Ethical Perspective on a Complex Issue.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research·2026
Same author

NeoCircle: pre- and post-operative circulating tumor DNA dynamics predicts survival in neoadjuvant-treated early breast cancer.

EMBO molecular medicine·2026
Same author

The Meaning of Surveillance in Women With a Hereditary Risk of Breast Cancer: A Hermeneutic Phenomenological Study.

Journal of clinical nursing·2026
Same author

Annotation and characterization of lesions in breast tomosynthesis images.

Radiation protection dosimetry·2026

相关实验视频

Updated: Sep 11, 2025

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

43.0K

通过使用基于深度学习的软件在查轮中评估个体内的乳腺扫描密度变化.

Jakob Olinder1,2, Daniel Förnvik3,4, Victor Dahlblom1,2

  • 1Lund University, Department of Translational Medicine, Radiology Diagnostics, Malmö, Sweden.

Journal of medical imaging (Bellingham, Wash.)
|August 18, 2025
PubMed
概括

随着时间的推移,乳腺密度自然会下降,特别是在乳腺密度较高的女性中. 乳腺密度的较慢下降可能表明未来乳腺癌诊断的风险更高.

关键词:
乳腺癌的风险 乳腺癌的风险乳腺癌查 乳腺癌查乳腺密度 乳腺密度深度学习是一种深度学习.纵向趋势是指纵向的趋势.乳房学 乳房学 乳房学

更多相关视频

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
15:48

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Published on: December 15, 2014

22.6K
Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer
07:53

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer

Published on: October 13, 2023

1.6K

相关实验视频

Last Updated: Sep 11, 2025

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

43.0K
Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
15:48

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Published on: December 15, 2014

22.6K
Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer
07:53

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer

Published on: October 13, 2023

1.6K

科学领域:

  • 放射学和成像科学 放射学和成像科学
  • 在瘤学瘤学.
  • 生物统计学 生物统计学

背景情况:

  • 乳房扫描乳腺密度是乳腺癌的重要风险因素.
  • 了解乳腺密度随时间变化对于准确的风险评估至关重要.

研究的目的:

  • 通过使用自动化软件在查轮中对个体内的乳房扫描密度的变化进行评估.
  • 为了确定乳腺密度的变化是否与未来的乳腺癌诊断有关.
  • 提供对乳腺密度随时间的演变的见解.

主要方法:

  • 2010年至2015年间接受过至少两轮查的女性乳房密度分析.
  • 使用基于深度学习的软件测量体积乳腺密度百分比 (VBD%).
  • 使用多重线性回归,调整共变量,研究VBD%变化和未来乳腺癌之间的关联.

主要成果:

  • 总共有26,056名女性被纳入该研究.
  • 在查之间,平均VBD%从10.7%降至10.3% (p < 0.001).
  • 最初乳腺密度较高的女性的VBD%的下降更明显,但未来乳腺癌诊断的女性的下降较小.

结论:

  • 随着时间的推移,观察到乳腺密度的变化可以增强风险评估工具.
  • 这些发现为开发未来基于风险的查策略提供了宝贵的见解.
  • 监测乳腺密度演变对于个性化乳腺癌风险评估很重要.