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相关概念视频

Computed Tomography01:10

Computed Tomography

4.4K
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...
4.4K
Electron Microscope Tomography and Single-particle Reconstruction01:07

Electron Microscope Tomography and Single-particle Reconstruction

2.4K
Transmission electron microscopy (TEM) can be used to determine the 3D structure of biological samples with the help of techniques such as electron microscope tomography and single-particle reconstruction. While single-particle reconstruction can examine macromolecules and macromolecular complexes in vitro conditions only, tomography permits the study of cell components or small cells in vivo.
Electron Tomography
Electron tomography can be performed either in TEM or STEM (scanning transmission...
2.4K

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Theoretical Prediction of Bias in Model-Based Material Decomposition.

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One-Step Material Decomposition Using Spectral Diffusion Posterior Sampling in Sparse-View Dual-Layer CT.

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相关实验视频

Updated: Jun 13, 2025

Three-Dimensional Particle Shape Analysis Using X-ray Computed Tomography: Experimental Procedure and Analysis Algorithms for Metal Powders
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对于光谱CT的联合材料分解和散射估计.

Altea Lorenzon1, Stephen Z Liu1, Xiao Jiang1

  • 1Biomedical Engineering at Johns Hopkins University.

Conference proceedings. International Conference on Image Formation in X-Ray Computed Tomography
|September 13, 2024
PubMed
概括

本研究引入了一种用于光谱计算机断层扫描 (CT) 的联合估计方法,以同时确定材料密度和散射谱. 这种方法有效地减少了来自未建模的散射的文物,改善了光谱CT成像质量.

科学领域:

  • 医学物理 医学物理
  • 图像重建 图像的重建
  • 计算机断层扫描 (CT) 是一种计算机断层扫描.

背景情况:

  • 精确的散射校正对于高质量的计算机断层扫描 (CT) 重建至关重要.
  • 光谱CT成像对分散校正中未建模的偏差特别敏感.

研究的目的:

  • 探索一种联合估计方法,用于在光谱CT中同时估计材料密度和散射特征.
  • 为了应对在光谱CT成像中未建模的散射所带来的挑战.

主要方法:

  • 采用了一步式基于模型的材料分解框架.
  • 进行了材料密度和散射特征的联合估计.
  • 该方法在模拟的光谱CT幻影数据上进行了测试,使用了参数添加散射模型.

主要成果:

  • 联合估计方法证明了减少未建模散射引起的工件的潜力.
  • 使用拟议的方法,材料密度估计得到了改进.
  • 进行了与未建模散射的场景进行比较.

结论:

  • 联合估计方法有望通过减轻与分散相关的工件来增强光谱CT成像.

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  • 这种方法可以在光谱CT中更准确地量化物质密度.
  • 对于临床应用,需要进一步研究.