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

Mesenchymal stem cell-derived microvesicles confer protection against rheumatoid arthritis-associated interstitial lung disease.

Stem cell research & therapy·2026
Same author

Reply: "Toward a more translational SS-ILD model: Sex differences, endpoints, and B cell targets".

Journal of immunology (Baltimore, Md. : 1950)·2026
Same author

Prediction of intravenous cyclophosphamide treatment efficacy in idiopathic inflammatory myopathies-associated interstitial lung disease patients: a nomogram based on radiomics and clinical factors.

BMC pulmonary medicine·2026
Same author

Applications, Progress, and Challenges of Surfactants in Chemical Mechanical Polishing for Copper Interconnects.

Langmuir : the ACS journal of surfaces and colloids·2026
Same author

Clinical epidemiology, determinants, and outcomes of severe viral encephalitis in Chinese children: a multicenter retrospective cohort study.

BMC infectious diseases·2026
Same author

ATM counteracts chromatin-bound cGAS during DNA replication.

Nature cell biology·2026

相关实验视频

Updated: Jan 14, 2026

Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans
10:23

Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans

Published on: September 8, 2023

3.6K

CeLR:一个基于变压器的回归网络,用于在高分辨率X射线成像中准确的头脑测量地标检测.

Jiakai Zhou, Yang Wang, Chaolin Huang

    IEEE transactions on medical imaging
    |January 12, 2026
    PubMed
    概括
    此摘要是机器生成的。

    一个新的以变压器为基础的网络,脑测地标回归 (CeLR),准确地定位X射线图像上的地标,用于正牙分析. 这种高效的方法可以在较低的计算成本下实现最先进的结果.

    更多相关视频

    A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
    04:23

    A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

    Published on: April 21, 2023

    2.3K
    Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
    05:49

    Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

    Published on: February 23, 2024

    1.3K

    相关实验视频

    Last Updated: Jan 14, 2026

    Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans
    10:23

    Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans

    Published on: September 8, 2023

    3.6K
    A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
    04:23

    A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

    Published on: April 21, 2023

    2.3K
    Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
    05:49

    Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

    Published on: February 23, 2024

    1.3K

    科学领域:

    • 医疗成像医学成像
    • 人工智能的人工智能
    • 矯正牙科 矯正牙科是一種矯正牙科.

    背景情况:

    • 准确的头测量地标定位对于自动化的正牙分析至关重要.
    • 当前的方法面临着高计算需求和复杂管道的挑战,限制了端到端优化.

    研究的目的:

    • 引入一个端到端的基于变压器的网络,即头度地标回归 (CeLR),用于在高分辨率的X射线图像上精确地标定位.
    • 为了提高头脑测量分析的准确性和效率.

    主要方法:

    • 开发了CeLR,一个端到端的变压器网络,使用特征提取器,参考编码器和具有交叉注意力的微调解码器.
    • 整合了一个无声化模块,以提高模型的稳定性.
    • 在公开的脑力测量数据集上进行评估.

    主要成果:

    • 在ISBI 2015挑战测试1数据集上,CeLR实现了最先进的性能,平均辐射误差 (MRE) 为0.98毫米,2毫米成功检测率 (SDR) 为89.82%.
    • 演示了91.3 GFLOP的计算成本,平衡了准确性和效率.
    • 展示了有效性和临床潜力.

    结论:

    • 拟议的CeLR网络提供了一个高度有效和高效的解决方案,用于脑测量地标回归.
    • CeLR对自动化正牙分析具有显著的临床潜力.
    • 基于变压器的方法可以实现端到端的优化,克服现有方法的局限性.