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

Computed Tomography01:10

Computed Tomography

7.9K
Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
7.9K

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

Longitudinal changes in epigenetic clocks predict survival in the InCHIANTI cohort.

Nature aging·2026
Same author

Shared and specific blood biomarkers for multimorbidity.

Nature medicine·2026
Same author

Compatibility and comparative analysis of chronological and biological aging between the legacy 450K and the EPIC v2.0 arrays.

Mechanisms of ageing and development·2025
Same author

The blood proteome predicts the impact of circulating factors on age-related mitochondrial health.

bioRxiv : the preprint server for biology·2025
Same author

DNA Methylation Signatures of Systemic Inflammation Are Associated With Brain Volume, Cognitive Trajectories, and Long-Term Dementia Risk.

Aging cell·2025
Same author

Pitfalls of defacing whole-head MRI: re-identification risk with diffusion models and compromised research potential.

Computers in biology and medicine·2025

相关实验视频

Updated: Jan 7, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

3.3K

通过深度条件生成模型减少腹部CT截面切片的位置变异.

Xin Yu1, Qi Yang1, Yucheng Tang2

  • 1Computer Science, Vanderbilt University, Nashville, TN, USA.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
|December 26, 2025
PubMed
概括

这项研究引入了C-SliceGen,这是一种新的方法,可以从纵向计算机断层扫描 (CT) 扫描中协调身体组成分析. 它减少了腹部切片的位置变异,改善了健康和衰老研究.

关键词:
腹部切片的生成过程身体组成 身体组成纵向数据协调与统一

更多相关视频

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
14:08

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

43.4K
Four-Dimensional CT Analysis Using Sequential 3D-3D Registration
05:05

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration

Published on: November 23, 2019

8.4K

相关实验视频

Last Updated: Jan 7, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

3.3K
Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
14:08

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

43.4K
Four-Dimensional CT Analysis Using Sequential 3D-3D Registration
05:05

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration

Published on: November 23, 2019

8.4K

科学领域:

  • 医疗成像医学成像
  • 人工智能的人工智能
  • 生物医学工程 生物医学工程

背景情况:

  • 2D腹部CT切片可以测量身体成分,这对于老化健康研究至关重要.
  • 纵向分析受到CT切片随时间变化的位置差异的阻碍.
  • 标准化这些切片对于准确的身体成分跟踪至关重要.

研究的目的:

  • 开发一种方法 (C-SliceGen) 来减少纵向2D腹部CT切片中的位置偏差.
  • 为了使更准确的身体组成分析随着时间的推移进行衰老研究.
  • 为了使不同脊椎水平的切片与目标切片协调.

主要方法:

  • 扩展条件生成模型以创建C-SliceGen.
  • 模型将任意的腹部切片作为输入,并生成定义的脊椎水平切片.
  • 估计潜空间的结构变化,以解释位置变异.

主要成果:

  • C-SliceGen产生高质量,现实的和类似的图像.
  • 在内部 (1170名受试者) 和BTCV MICCAI (50名受试者) 数据集上验证.
  • 在BLSA数据集 (20名受试者) 中协调肌肉和内脏脂肪区域的纵向切片.

结论:

  • C-SliceGen有效地减少了纵向腹部CT切片的位置变异.
  • 为单片纵向分析提供了协调片的有希望的方法.
  • 在衰老研究中更准确地跟踪身体成分.