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相关概念视频

Computed Tomography01:10

Computed Tomography

9.3K
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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Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

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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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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...
1.1K
Radiological Investigation II: MRI and Ventilation Perfusion Scan01:30

Radiological Investigation II: MRI and Ventilation Perfusion Scan

792
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...
792
Radiological Investigation I: X-ray and CT01:30

Radiological Investigation I: X-ray and CT

1.4K
Radiological investigations, including X-rays and computed tomography (CT) scans, are critical for diagnosing and evaluating various medical conditions. These imaging techniques provide valuable insights into the body's internal structures, aiding in the detection of abnormalities, assessment of disease progression, and development of treatment strategies. This article delves into two primary radiological investigations, chest X-rays and CT scans, outlining their purpose, procedures, and...
1.4K
X-ray Imaging01:24

X-ray Imaging

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German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with...
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相关实验视频

Updated: Mar 12, 2026

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
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Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping

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机器幻觉在放射学中的分类.

Frank J Brooks1, Mark A Anastasio1

  • 1Department of Bioengineering, Grainger College of Engineering, University of Illinois Urbana-Champaign, 1406 W. Green St, 1102 Everitt Lab MC 278, Urbana, IL 61801.

Radiology. Artificial intelligence
|March 11, 2026
PubMed
概括

在生成AI中定义机器幻觉对于放射学至关重要. 这项研究澄清了不同的解释,以提高AI可信度和临床使用的沟通.

科学领域:

  • 医疗成像中的人工智能
  • 放射学 人工智能 评估
  • 生成式人工智能性能指标

背景情况:

  • 在放射学中评估生成性AI需要对机器幻觉有明确的定义.
  • 目前幻觉定义的模糊性阻碍了可靠的AI评估和临床采用.
  • 对幻觉的不同解释导致了相互矛盾的AI系统特征.

研究的目的:

  • 在AI中提供不同机器幻觉概念的非技术解释.
  • 为放射科医生提出与机器幻觉相关的分类学.
  • 在放射学中评估生成AI性能时减少模两可.

主要方法:

  • 解释机器幻觉的两个概念之间的根本差异.
  • 使用放射学家熟悉的术语开发分类学.
  • 对部署的人工智能系统的输出应急情况的划分.

主要成果:

  • 澄清机器幻觉定义中的核心差异.
  • 一个拟议的分类学来根据解释对AI输出进行分类.
  • 框架,使人工智能评估与临床用例保持一致.

结论:

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Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

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Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
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  • 清晰的分类学减少了生成AI幻觉评估中的模糊性.
  • 标准化定义有助于利益相关者之间更好的沟通.
  • 更好的理解提高了AI在放射学中的可靠性和实用性.