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相关概念视频

Computed Tomography01:10

Computed Tomography

4.6K
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 for Cardiovascular System V: CT01:28

Imaging Studies for Cardiovascular System V: CT

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Cardiac computed tomography (CT) scanning is an advanced cardiac imaging technique that utilizes CT technology, with or without intravenous (IV) contrast, to produce accurate cross-sectional virtual slices of specific areas of the heart, coronary circulation, and major blood vessels such as the aorta, pulmonary veins, and arteries. The computer processes these slices to generate three-dimensional images. Multidetector CT (MDCT) is a rapid form of CT scanning that captures multiple slices...
42
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

28
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...
28
Imaging Studies I: CT and MRI01:14

Imaging Studies I: CT and MRI

280
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...
280
Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT01:25

Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT

39
Calcium-Scoring CT ScanA calcium-scoring CT scan, also known as coronary artery calcium (CAC) scan, detects calcium deposits in the coronary arteries. This test assesses the risk of coronary artery disease (CAD), which can lead to cardiovascular events such as angina, heart failure, and sudden cardiac arrest.A calcium-scoring CT scan is generally recommended for individuals at intermediate risk of CAD without symptoms. It includes:Men aged 40-75 and women aged 50-75: Especially those with a...
39
Deconvolution01:20

Deconvolution

188
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
188

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相关实验视频

Updated: Jul 19, 2025

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

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基于无监督学习的双域方法用于低剂量CT无噪声.

Jie Yu1, Huitao Zhang1,2, Peng Zhang1

  • 1School of Mathematical Sciences, Capital Normal University, Beijing, 100048, People's Republic of China.

Physics in medicine and biology
|August 11, 2023
PubMed
概括

这项研究引入了低剂量CT (LDCT) 成像的无监督深度学习方法,克服了对数据的挑战. 这种新的双域方法有效地消除了图像,为CT扫描中的辐射剂量减少提供了一个有希望的替代方案.

关键词:
双域方法是双域方法.低剂量CTCT的使用.无人监督的无噪声处理

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科学领域:

  • 医疗成像医学成像
  • 计算成像技术的成像
  • 医疗保健中的人工智能

背景情况:

  • 低剂量计算机断层扫描 (LDCT) 对于减少医学诊断中的辐射暴露至关重要.
  • 深度学习方法已经推进了LDCT成像,但在配对的低剂量和高剂量数据集方面面临挑战.
  • 监督学习需要几何匹配的数据集,这是LDCT的重大局限性.

研究的目的:

  • 开发一种基于无监督学习的低剂量CT (LDCT) 成像方法.
  • 为了应对在监督的LDCT中获取几何配对数据集的挑战.
  • 为了提高LDCT中的图像质量,同时尽量减少辐射剂量.

主要方法:

  • 一种双域无监督学习方法,用于LDCT的宣传.
  • 阶段1:使用Noise2Self方法对统计学上独立的噪声进行投影域的无声化.
  • 第二阶段:代增强,将生成模型先验与代重建结合起来.

主要成果:

  • 与现有方法相比,拟议的无监督方法表现出优越的脱性能.
  • 该方法实现了最高的结构相似度指数 (SSIM) 测量对无色图像.
  • 实验结果验证了双域方法的有效性.

结论:

  • 基于无监督学习的方法是对LDCT成像监督技术的可行替代方案.
  • 当LDCT的标记数据集稀缺时,这种方法特别有益.
  • 该方法为推进安全有效的CT成像实践提供了一个有希望的方向.