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Related Concept Videos

Computed Tomography01:10

Computed Tomography

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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Related Experiment Video

Updated: May 18, 2026

Management of Respiratory Motion Artefacts in 18F-fluorodeoxyglucose Positron Emission Tomography using an Amplitude-Based Optimal Respiratory Gating Algorithm
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Management of Respiratory Motion Artefacts in 18F-fluorodeoxyglucose Positron Emission Tomography using an Amplitude-Based Optimal Respiratory Gating Algorithm

Published on: July 23, 2020

Noise reduction with low dose CT data based on a modified ROF model.

Yining Zhu1, Mengliu Zhao, Yunsong Zhao

  • 1The CT Laboratory, School of Mathematics, Capital Normal University, Beijing, 100048, China.

Optics Express
|October 6, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a modified ROF model to reduce noise in low-dose CT scans. The new method improves image quality, offering a better solution for radiation dose reduction in computed tomography.

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X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging
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Last Updated: May 18, 2026

Management of Respiratory Motion Artefacts in 18F-fluorodeoxyglucose Positron Emission Tomography using an Amplitude-Based Optimal Respiratory Gating Algorithm
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X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging
08:30

X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging

Published on: September 11, 2011

Area of Science:

  • Medical Imaging
  • Image Processing
  • Computational Science

Background:

  • Low-dose computed tomography (CT) is crucial for reducing radiation exposure.
  • High noise levels in low-dose CT raw data degrade reconstructed image quality.
  • Existing denoising methods struggle with the specific noise characteristics of low-dose CT.

Purpose of the Study:

  • To develop an advanced denoising model for low-dose CT measurement data.
  • To address the challenge of noise pollution in low-dose CT imaging.
  • To improve the quality of reconstructed CT images obtained with reduced radiation doses.

Main Methods:

  • A modified Rudin-Osher-Fatemi (ROF) model was developed.
  • The model specifically targets Poisson noise inherent in low-dose CT data.
  • The proposed method processes raw CT measurement data before image reconstruction.

Main Results:

  • The modified ROF model effectively reduced noise in low-dose CT data.
  • CT images reconstructed from denoised data showed superior quality.
  • Performance was compared favorably against the original ROF model and bilateral filtering.

Conclusions:

  • The modified ROF model offers a significant improvement for low-dose CT denoising.
  • This approach enhances the diagnostic quality of CT images while minimizing radiation exposure.
  • The proposed method represents a valuable advancement in medical imaging technology.