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

Assessment of Diffusion and Perfusion01:17

Assessment of Diffusion and Perfusion

1.0K
Understanding and evaluating diffusion and perfusion is critical in assessing a patient's respiratory and circulatory health. These processes play key roles in maintaining the body's internal environment, ensuring that tissues receive adequate oxygen while waste products are efficiently removed.
The Role of Diffusion in Respiration
Diffusion is the process by which molecules move from an area of higher concentration to an area of lower concentration. In the respiratory system, this...
1.0K
Diffusion01:12

Diffusion

194.1K
Diffusion is the passive movement of substances down their concentration gradients—requiring no expenditure of cellular energy. Substances, such as molecules or ions, diffuse from an area of high concentration to an area of low concentration in the cytosol or across membranes. Eventually, the concentration will even out, with the substance moving randomly but causing no net change in concentration. Such a state is called dynamic equilibrium, which is essential for maintaining overall...
194.1K
Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models

119
Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...
119
Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

5.3K
Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
5.3K
Positron Emission Tomography01:29

Positron Emission Tomography

4.3K
Positron emission tomography (PET) is a medical imaging technique involving radiopharmaceuticals — substances that emit short-lived radiation. Although the first PET scanner was introduced in 1961, it took 15 more years before radiopharmaceuticals were combined with the technique and revolutionized its potential.
One of the main requirements of a PET scan is a positron-emitting radioisotope, which is produced in a cyclotron and then attached to a substance used by the part of the body...
4.3K
Radiological Investigation II: MRI and Ventilation Perfusion Scan01:30

Radiological Investigation II: MRI and Ventilation Perfusion Scan

156
Description
Magnetic Resonance Imaging (MRI) and Ventilation Perfusion Scans are two radiological investigations that offer detailed diagnostic images of the body, particularly lung structures.
MRI
MRI uses magnetic fields and radiofrequency signals to distinguish between normal and abnormal tissues. This technology provides a more detailed diagnostic image than CT scans, enabling it to characterize pulmonary nodules, stage bronchogenic carcinoma, and evaluate inflammatory activity in...
156

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

A clinically anchored radiomics dictionary for explainable TI-RADS-based thyroid nodule classification in ultrasound; dictionary version TU1.0.

European journal of radiology·2026
Same author

Robust Semi-Supervised CT Radiomics for Lung Cancer Prognosis: Cost-Effective Learning with Limited Labels and SHAP Interpretation.

IEEE transactions on bio-medical engineering·2026
Same author

Deep learning-based Desikan-Killiany parcellation of the brain using diffusion MRI.

Scientific reports·2026
Same author

MonoUNet: A Robust Tiny Neural Network for Automated Knee Cartilage Segmentation on Point-of-care Ultrasound Devices.

Ultrasound in medicine & biology·2026
Same author

Handcrafted vs. Deep Radiomics vs. Fusion vs. Deep Learning: A Comprehensive Review of Machine Learning -Based Cancer Outcome Prediction in PET and SPECT Imaging.

Journal of imaging informatics in medicine·2026
Same author

Multifeature Ultrasound-Based Classification for Breast Lesions: A Comparative Study of PONS Image Enhancement Technology.

Mayo Clinic proceedings. Innovations, quality & outcomes·2026

相关实验视频

Updated: Jul 27, 2025

Diffusion Imaging in the Rat Cervical Spinal Cord
10:46

Diffusion Imaging in the Rat Cervical Spinal Cord

Published on: April 7, 2015

11.8K

医学成像中的扩散模型:一个全面的调查调查.

Amirhossein Kazerouni1, Ehsan Khodapanah Aghdam2, Moein Heidari1

  • 1School of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran.

Medical image analysis
|June 9, 2023
PubMed
概括

扩散模型是深度学习的强大生成工具,现在越来越多地应用于医学成像,用于重建和细分等任务. 这份调查提供了对它们的理论,应用和医疗领域未来方向的全面指南.

关键词:
脱扩散模型的脱.扩散模型的扩散模型.生成型模型是一种生成型模型.医疗应用 医学应用医学成像医学成像噪音条件下得分网络 噪音条件下得分网络基于得分的模型.调查 调查 调查 调查

更多相关视频

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
17:06

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

26.3K
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
09:33

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

28.5K

相关实验视频

Last Updated: Jul 27, 2025

Diffusion Imaging in the Rat Cervical Spinal Cord
10:46

Diffusion Imaging in the Rat Cervical Spinal Cord

Published on: April 7, 2015

11.8K
Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
17:06

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

26.3K
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
09:33

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

28.5K

科学领域:

  • 人工智能的人工智能
  • 医疗成像医学成像
  • 计算机视觉 计算机视觉

背景情况:

  • 无光散发模型是生成模型,在数据生成质量和覆盖率方面表现出色.
  • 由于计算机视觉的进步,这些模型在医学成像中越来越受欢迎.
  • 尽管计算成本高,但它们在医疗应用中的潜力是显著的.

研究的目的:

  • 为医疗成像中的扩散模型提供全面的概述.
  • 根据应用,模式,器官和算法系统地分类扩散模型.
  • 引导研究人员通过这个领域不断增长的工作.

主要方法:

  • 介绍扩散模型的理论基础及其三个主要框架:扩散概率模型,噪声条件下得分网络和随机微分方程.
  • 医学中扩散模型的系统分类和多视角分类.
  • 广泛的应用程序的审查,包括图像对图像的翻译,重建,注册,分类,细分,无声化,生成和异常检测.

主要成果:

  • 扩散模型在各种医学成像任务中展示了广泛的适用性.
  • 该调查对现有研究进行了分类,突出了关键算法及其在各种医疗环境中的使用.
  • 讨论了实际的用例和局限性,以及未来的研究方向.

结论:

  • 扩散模型为推进医学成像分析和生成提供了一个有希望的途径.
  • 需要进一步的研究来解决局限性,并在临床环境中充分发挥其潜力.
  • 提供了审查研究的开源存储库,以促进正在进行的研究和开发.