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

相关实验视频

Updated: Jan 13, 2026

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.7K

在鼠标骨中使用多视图X射线图像进行异常分类的层次深度学习:卷积自编码器与ConvNeXt对比.

Muhammad M Jawaid1, Rasneer S Bains2, Sara Wells2

  • 1School of Engineering & Physical Sciences, College of Health & Science, University of Lincoln, Brayford Pool, Lincoln LN6 7TS, UK.

Journal of imaging
|October 28, 2025
PubMed
概括

多视图成像显著提高了小鼠的骨异常检测,特别是复杂的多标签病例. 具有多个视图的等级学习比单个视图方法提高了分类准确性.

相关概念视频

Classification of Bones01:18

Classification of Bones

9.5K
The bones of the human skeletal system are of varied shapes, sizes, and functions. They can be classified based on their shape and function into four major classes: long bones, short bones, flat bones, and irregular bones. Some classifications include a fifth type, the sesamoid bones, as a separate class, whereas others categorize them under short bones.
Long and Short Bones
The appendicular skeleton, particularly the upper and lower limbs, is primarily made of long and short bones. The...
9.5K

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

Critical uncertainties in preclinical research: Navigating trust, technology, and ethics.

Neuroscience applied·2026
Same author

Correction: Establishing standardized transthoracic echocardiography reference ranges for mouse models: insights into the impact of anesthesia, sex, and age.

Frontiers in cardiovascular medicine·2026
Same author

Challenges and expectations on the use of automated home cage monitoring for advancing laboratory animal care and welfare.

Laboratory animals·2026
Same author

Long-acting parathyroid hormone receptor agonist rectifies hypocalcemia in autosomal dominant hypocalcemia type 1 mice.

The Journal of clinical investigation·2026
Same author

Establishing standardized transthoracic echocardiography reference ranges for mouse models: insights into the impact of anesthesia, sex, and age.

Frontiers in cardiovascular medicine·2026
Same author

International Mouse Phenotyping Consortium: Investigating gene function and providing insights into human disease.

bioRxiv : the preprint server for biology·2025

科学领域:

  • 生物医学成像学 生物医学成像学
  • 机器学习是机器学习.
  • 计算生物学是一种计算生物学.

背景情况:

  • 单视图异常检测缺乏多标签问题的上下文.
  • 多视图成像为分类任务提供更丰富的上下文信息.

研究的目的:

  • 为了评估多视图 (MV) 图像数据与层次学习用于骨异常检测的有效性.
  • 在多标签环境中,将MV分类与单视图方法的性能进行比较.

主要方法:

  • 从170,958张国际老鼠表型化联盟 (IMPC) 图像中策划了一个样本智能的MV数据集.
  • 开发了两种使用ConvNeXT和卷积自编码器 (CAE) 骨架的等级分类框架.
  • 训练有素的模型在三个层次的层次上增加了解剖细粒度.

主要成果:

  • MV分类的表现与最高层次层级的单个视图相比较 (L1,平均AUC为0.95).
  • 使用MV数据的等级模型与单个视图相比,在较低的水平 (L2和L3) 显著改善了分类 (例如,L2:DV 0.65,LV 0.76,MV 0.87;L3:DV 0.54,LV 0.59,MV 0.82).
  • 无论是ConvNeXT还是CAE架构都展示了MV数据在检测特定骨异常方面的优势.
关键词:
卷积式自动编码器的自动编码器阶层式的学习学习.鼠标表型化 鼠标表型化多视图表示的多视图表示.骨异常是一种骨异常.

相关实验视频

Last Updated: Jan 13, 2026

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.7K

结论:

  • 多视图图像数据与层次学习相结合,有利于检测骨异常.
  • 这种方法通过提供增强的上下文信息,有效地解决了多标签异常检测方面的挑战.