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

8.0K
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...
8.0K
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

283
DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
283

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 authorSame journal

Image Reconstruction with Maclaurin Series Expansion.

International journal of biomedical research & practice·2026
Same author

A Higher-Order Ising Model with Gradient-Free Update.

Axioms·2026
Same author

Radon Inversion Reconstruction for Kooshball-Like Sampling Trajectory in Cine.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

Mitigating the Drawbacks of the L<sub>0</sub> Norm and the Total Variation Norm.

Axioms·2025
Same authorSame journal

One-Step Image Reconstruction for Cine MRI with a Quadratic Constraint.

International journal of biomedical research & practice·2024
Same author

Deterministic Versus Nondeterministic Optimization Algorithms for the Restricted Boltzmann Machine.

Journal of computational and cognitive engineering·2024
Same journal

Better than the Total Variation Regularization.

International journal of biomedical research & practice·2024
查看所有相关文章

相关实验视频

Updated: Jan 16, 2026

Author Spotlight: Integrated Photoacoustic, Ultrasound, and Angiographic Tomography (PAUSAT) for NonInvasive Whole-Brain Imaging of Ischemic Stroke
06:45

Author Spotlight: Integrated Photoacoustic, Ultrasound, and Angiographic Tomography (PAUSAT) for NonInvasive Whole-Brain Imaging of Ischemic Stroke

Published on: June 2, 2023

2.2K

使用神经网络作为目标函数的有限角度断层扫描.

Gengsheng L Zeng1

  • 1Department of Computer Science, Utah Valley University, Orem, USA.

International journal of biomedical research & practice
|January 15, 2026
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的神经网络贝叶斯式术语,以改善有限角度断层扫描图像重建. 这种方法增强了图像特征,超出了传统的总变化,预计在未确定系统中获得更好的结果.

关键词:
贝叶斯语 贝叶斯语 贝叶斯语 贝叶斯语"分类器"是指分类器.卷积神经网络是一种卷积神经网络.图像重建 图像重建这是一个反向问题.有限角断层扫描技术有限角断层扫描技术优化优化 优化优化断层扫描 (Tomography) 是一个专业的技术.样本不足的数据不足的数据

更多相关视频

Deep Learning-Based Segmentation of Cryo-Electron Tomograms
10:25

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Published on: November 11, 2022

10.6K
3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography
07:01

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography

Published on: October 24, 2019

10.2K

相关实验视频

Last Updated: Jan 16, 2026

Author Spotlight: Integrated Photoacoustic, Ultrasound, and Angiographic Tomography (PAUSAT) for NonInvasive Whole-Brain Imaging of Ischemic Stroke
06:45

Author Spotlight: Integrated Photoacoustic, Ultrasound, and Angiographic Tomography (PAUSAT) for NonInvasive Whole-Brain Imaging of Ischemic Stroke

Published on: June 2, 2023

2.2K
Deep Learning-Based Segmentation of Cryo-Electron Tomograms
10:25

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Published on: November 11, 2022

10.6K
3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography
07:01

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography

Published on: October 24, 2019

10.2K

科学领域:

  • 医疗成像医学成像
  • 计算科学 计算科学
  • 人工智能的人工智能

背景情况:

  • 有限角断层扫描成像系统遭受不确定方程,导致不切实际的重建.
  • 在代优化中使用贝叶斯式术语来增强数据对于有用的图像重建至关重要.
  • 当前最先进的方法使用总变化 (TV) 规范进行图像光滑和边缘保护.

研究的目的:

  • 介绍一个新的贝叶斯术语用于有限角度断层扫描重建.
  • 利用神经网络作为一种新的增强信息形式.
  • 通过结合更丰富的图像功能来提高图像重建质量.

主要方法:

  • 开发了一个神经网络分类器,训练在全角和有限角投影图像上.
  • 在代优化框架内将神经网络集成为贝叶斯术语.
  • 将拟议的方法与传统的总变化 (TV) 标准进行比较.

主要成果:

  • 神经网络贝叶斯式术语提供了比电视标准更全面的图像特征.
  • 计算机模拟证明了增强图像重建质量的潜力.
  • 预计拟议的方法将在未确定的断层扫描系统中产生更好的重建.

结论:

  • 一个新的基于神经网络的贝叶斯术语为有限角度断层扫描提供了有前途的进步.
  • 这种方法通过捕捉更复杂的图像细节,超越了电视规范的局限性.
  • 通过计算机模拟进行进一步验证,表明改善诊断成像的巨大潜力.