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Related Concept Videos

Computed Tomography01:10

Computed Tomography

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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 III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

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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...
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Updated: Sep 22, 2025

Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph
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Image reconstruction method for limited-angle CT based on total variation minimization using guided image filtering.

Jiaxi Wang1, Yuanyuan Yue2, Chengxiang Wang3

  • 1College of Computer, Chengdu University, Chengdu, 610100, China.

Medical & Biological Engineering & Computing
|May 20, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method using guided image filtering to enhance computed tomography (CT) image reconstruction. The technique effectively reduces artifacts and noise in limited-angle CT scans, improving image quality and structural preservation.

Keywords:
Computed tomography (CT)Guided image filteringImage reconstructionLimited-angleTotal variation

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Area of Science:

  • Medical Imaging
  • Computational Imaging
  • Image Reconstruction

Background:

  • Computed tomography (CT) applications often face limited scanning angles due to practical constraints.
  • Limited-angle CT data leads to artifacts in classical image reconstruction, degrading image quality.
  • Existing methods like Total Variation minimization with L1 norm (TVL1) struggle with edge artifacts in limited-angle CT, while L0 norm (TVL0) methods have limitations with reduced scanning ranges.

Purpose of the Study:

  • To improve the quality of reconstructed images in limited-angle CT.
  • To address and suppress limited-angle artifacts and noise.
  • To enhance structural preservation in CT images reconstructed from limited angular data.

Main Methods:

  • A novel image reconstruction method combining Total Variation minimization with L1 norm (TVL1) and L0 norm (TVL0) was developed.
  • Guided Image Filtering (GIF) was employed to transfer image characteristics between TVL1 and TVL0 reconstructions.
  • The proposed method integrates the strengths of TVL1 and TVL0 methods using GIF for improved artifact suppression and structure preservation.

Main Results:

  • The proposed method demonstrated superior performance in preserving image structures compared to existing techniques.
  • Significant suppression of limited-angle artifacts was achieved.
  • The method effectively reduced noise in the reconstructed CT images.

Conclusions:

  • The integration of GIF with TVL1 and TVL0 methods offers a promising approach for high-quality limited-angle CT image reconstruction.
  • This technique effectively mitigates artifacts and enhances image fidelity.
  • The findings suggest a significant advancement in addressing the challenges of limited-angle CT imaging.