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相关概念视频

Computed Tomography01:10

Computed Tomography

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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...
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Imaging Studies I: CT and MRI01:14

Imaging Studies I: CT and MRI

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Introduction: MRI and CT scans are crucial advancements in medical imaging techniques, playing a vital role in diagnosing conditions related to the gastrointestinal (GI) system. Each scan serves distinct purposes, targets specific areas, and requires unique nursing duties.
Description of the Procedures
Computed Tomography (CT) scan:
Computed Tomography (CT) scans use X-ray technology to generate detailed images of bones, organs, and tissues. During the scan, the patient lies on a moving table...
959
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

429
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...
429
Transformers01:26

Transformers

2.0K
A device that transforms voltages from one value to another using induction is called a transformer. A transformer consists of two separate coils, or windings, wrapped around the same soft iron core. However, they are electrically insulated from each other.
The iron core has a substantial relative permeability. Therefore, the magnetic field lines generated due to the current in one winding are almost entirely confined within the core, such that the same magnetic flux permeates each turn of both...
2.0K
Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

9.9K
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...
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Three-Winding Transformers01:19

Three-Winding Transformers

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Three identical single-phase transformers can be configured to form a three-phase transformer connection, which involves high-voltage and low-voltage windings. The high-voltage windings are denoted by capital letters A-B-C, while the low-voltage windings are labeled with lowercase letters a-b-c, representing their respective phases. This notation helps distinguish between the high and low voltage sides of the transformer.
In the per-unit equivalent circuit of a grounded Y-Y three-phase...
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相关实验视频

Updated: Feb 20, 2026

Author Spotlight: Optimized Lung MRI Protocol with Computationally Efficient Reconstruction Methods
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Author Spotlight: Optimized Lung MRI Protocol with Computationally Efficient Reconstruction Methods

Published on: September 6, 2024

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TranIU-Net:基于隐式无滚转变压器的指示性电断层成像.

Binchun Lu, Lidan Fu, Juntao Ren

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
    |February 18, 2026
    PubMed
    概括

    本研究介绍了TranIU-Net,这是一个新的深度展开变压器,用于改进图像重建. 它通过整合本地和非本地依赖来克服现有方法的局限性,以获得更好的准确性和系统设计.

    科学领域:

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

    背景情况:

    • 深度展开网络结合了数据驱动和模型驱动的图像重建方法.
    • 现有的方法面临着诸如不充分的代,有限的受感场和与物理系统的隔离等挑战.

    研究的目的:

    • 提出TranIU-Net,一个新的隐性展开变压器架构,用于增强图像重建.
    • 通过整合本地和非本地依赖和指导系统设计来解决当前无线网络的局限性.

    主要方法:

    • TranIU-Net将近位梯度算法展开成一个具有结构解释性的可训练网络.
    • 嵌入式变压器模块通过混合受体场和显著性估计器捕获多尺度信息.
    • 一个隐式映射保证在无限深度与恒定内存成本的收.

    主要成果:

    • 在电断层扫描重建中,TranIU-Net在最先进的方法中表现出优越的性能.
    • 该架构在各种场景中实现了改进的定量和质量重建结果.
    • 该方法有效地弥合了重建算法和成像系统之间的差距.

    结论:

    • 对于图像重建任务,TranIU-Net提供了一个强大而高效的解决方案.

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  • 拟议的架构通过将先进的深度学习技术与基于模型的原则相结合,推动了该领域的发展.
  • 这项工作通过考虑内在的图像相关性和系统设计,促进了更好的重建质量.