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

Atomic Nuclei: Nuclear Relaxation Processes01:23

Atomic Nuclei: Nuclear Relaxation Processes

1.4K
In the absence of an external magnetic field, nuclear spin states are degenerate and randomly oriented. When a magnetic field is applied, the spins begin to precess and orient themselves along (lower energy) or against (higher energy) the direction of the field. At equilibrium, a slight excess population of spins exists in the lower energy state. Because the direction of the magnetic field is fixed as the z-axis,  the precessing magnetic moments are randomly oriented around the z-axis.
1.4K
Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

10.5K
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...
10.5K
Atomic Nuclei: Types of Nuclear Relaxation01:28

Atomic Nuclei: Types of Nuclear Relaxation

1.2K
Nuclear relaxation restores the equilibrium population imbalance and can occur via spin–lattice or spin–spin mechanisms, which are first-order exponential decay processes.
In spin–lattice or longitudinal relaxation, the excited spins exchange energy with the surrounding lattice as they return to the lower energy level. Among several mechanisms that contribute to spin–lattice relaxation, magnetic dipolar interactions are significant. Here, the excited nucleus transfers...
1.2K
Carrier Transport01:21

Carrier Transport

1.2K
The generation of electrical current in semiconductors is fundamentally driven by two mechanisms: drift and diffusion. These processes are essential for the functionality and performance of semiconductor-based devices.
Drift Current:
The drift of charge carriers is started by an external electric field (E). Charged particles, such as electrons and holes, experience an acceleration between collisions with lattice atoms. For electrons, this results in a drift velocity (vd) given by:
1.2K
Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

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

468
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...
468

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

J-Score: Joint Distribution Learning With Score-Based Diffusion for Accelerating T1ρ Mapping.

IEEE transactions on medical imaging·2025
Same author

Continuous-wave terahertz quantum cascade lasers based on quasi-flatband BIC and 2D dual-patch arrays.

Optics express·2025
Same author

Physics-Informed DeepMRI: k-Space Interpolation Meets Heat Diffusion.

IEEE transactions on medical imaging·2024
Same author

Synthesizing PET images from high-field and ultra-high-field MR images using joint diffusion attention model.

Medical physics·2024
Same author

A Two-Stage Generative Model with CycleGAN and Joint Diffusion for MRI-based Brain Tumor Detection.

IEEE journal of biomedical and health informatics·2024
Same author

High-Frequency Space Diffusion Model for Accelerated MRI.

IEEE transactions on medical imaging·2024
Same journal

Physiology-guided Self-supervised Learning for Simultaneous Dual-Tracer PET Separation.

IEEE transactions on medical imaging·2026
Same journal

Informed-Exploration Reinforcement Learning for Automated Virtual Coronary Intervention Planning.

IEEE transactions on medical imaging·2026
Same journal

4D Reconstruction of Fetal Left Ventricle from Echocardiography via 2.5D Radial Segmentation and Graph-Fourier Reconstruction.

IEEE transactions on medical imaging·2026
Same journal

Generalised Medical Phrase Grounding.

IEEE transactions on medical imaging·2026
Same journal

EndoLRMGS: Combining Large Reconstruction Modelling and Gaussian Splatting for Complete Endoscopic Scene Reconstruction.

IEEE transactions on medical imaging·2026
Same journal

A Neural-Analytical Fusion Scatter Correction Method for Multi-Source CT Using Equivalent High-Order Scatter.

IEEE transactions on medical imaging·2026
查看所有相关文章

相关实验视频

Updated: Apr 14, 2026

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

27.2K

SPIRiT-扩散:用于加速MRI的自我一致性驱动扩散模型.

Zhuo-Xu Cui, Chentao Cao, Yue Wang

    IEEE transactions on medical imaging
    |October 3, 2024
    PubMed
    概括
    此摘要是机器生成的。

    SPIRiT-Diffusion引入了一种用于磁共振成像 (MRI) 重建的新型k空间插值方法. 这种以模型为驱动的扩散方法提高了重建质量,甚至在高速加速速度下也超过了图像域方法.

    更多相关视频

    Diffusion Imaging in the Rat Cervical Spinal Cord
    10:46

    Diffusion Imaging in the Rat Cervical Spinal Cord

    Published on: April 7, 2015

    12.3K
    A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia
    09:59

    A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia

    Published on: September 16, 2017

    14.7K

    相关实验视频

    Last Updated: Apr 14, 2026

    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

    27.2K
    Diffusion Imaging in the Rat Cervical Spinal Cord
    10:46

    Diffusion Imaging in the Rat Cervical Spinal Cord

    Published on: April 7, 2015

    12.3K
    A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia
    09:59

    A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia

    Published on: September 16, 2017

    14.7K

    科学领域:

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

    背景情况:

    • 扩散模型在图像生成和磁共振成像 (MRI) 重建方面出色.
    • 目前基于扩散模型的MRI重建方法在图像域中运行,由于线圈灵敏度图的不准确性,质量受到限制.
    • k空间插值提供了一个解决方案,但与传统的扩散模型不兼容.

    研究的目的:

    • 开发一种用于MRI重建中的k空间插值的新型扩散模型.
    • 通过结合k空间物理来解决图像域扩散模型的局限性.
    • 为了提高MRI重建质量和强度,防止线圈灵敏度地图错误.

    主要方法:

    • 介绍了SPIRiT-Diffusion,这是一个以SPIRiT方法为灵感的k空间插值的扩散模型.
    • 使用 SPIRiT 代求解器的 k 空间物理先验,制定了一个新的随机微分方程 (SDE).
    • 在k空间中执行扩散过程以进行数据插入,称为模型驱动扩散.

    主要成果:

    • 与图像域重建方法相比,SPIRiT-扩散显示出更高的性能.
    • 在10的显著加速因子下实现了高质量的重建.
    • 在3D关节内和状血管壁成像数据集上验证.

    结论:

    • 在MRI重建中,SPIRiT-Diffusion有效地执行k空间插值.
    • 模型驱动的扩散方法使扩散过程与物理先验保持一致,增强重建.
    • 这种方法为加速和强大的MRI采集提供了一个有希望的方向.