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相关概念视频

Computed Tomography01:10

Computed Tomography

4.5K
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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CHEMONO: a Cherenkov-Only Monolithic Detector for PGI in Proton Range Verification.

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相关实验视频

Updated: Jul 1, 2025

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
14:08

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

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基于学习的光谱CT系统审查

Alexandre Bousse1, Venkata Sai Sundar Kandarpa1, Simon Rit2

  • 1LaTIM, Inserm UMR 1101, Université de Bretagne Occidentale, 29238 Brest, France.

IEEE transactions on radiation and plasma medical sciences
|March 13, 2024
PubMed
概括
此摘要是机器生成的。

光谱计算机断层扫描 (CT) 提供了比传统CT更先进的成像技术. 机器学习技术正在出现,以克服光谱CT文物并改善临床应用.

关键词:
人工智能 (AI) 是一种人工智能.深度学习 (Deep Learning) 是一种深度学习.双能CT (DECT) 是一种双能CT.机器学习 机器学习光子计数CT (PCCT) 是一种光子计数CT.

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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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Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss
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Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

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相关实验视频

Last Updated: Jul 1, 2025

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
14:08

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

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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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科学领域:

  • 医学成像医学成像
  • 放射学 放射学是一门学科.
  • 计算机断层扫描 (CT) 是一种计算机断层扫描.

背景情况:

  • 光谱计算机断层扫描 (CT) 与传统的单能CT相比,是一个进步.
  • 主要形式包括双能CT (DECT) 和光子计数CT (PCCT).
  • 这些技术提高了图像质量,使材料分解成为可能,并允许特征量化.

研究的目的:

  • 审查光谱CT的最新数据驱动技术.
  • 为应对光谱CT数据和图像所固有的挑战和工件.
  • 突出机器学习应用在克服光谱CT的局限性.

主要方法:

  • 对用于光谱CT的机器学习技术的审查.
  • 对数据驱动的方法进行分析,以减少人工制造物的减少.
  • 检查材料分解和特征量化的方法.

主要成果:

  • 机器学习在减轻光谱CT文物方面显示出显著的希望.
  • 数据驱动技术提高图像质量和诊断准确度.
  • ML使材料分解和定量分析得到了改进.

结论:

  • 机器学习对于克服光谱CT挑战至关重要.
  • 先进的技术对于光谱CT的更广泛的临床采用至关重要.
  • 未来的研究应该专注于用于光谱CT的强大的ML算法.