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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

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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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Related Experiment Video

Updated: Nov 11, 2025

Protocol for the Evaluation of MRI Artifacts Caused by Metal Implants to Assess the Suitability of Implants and the Vulnerability of Pulse Sequences
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Inpainting-filtering for metal artifact reduction (IMIF-MAR) in computed tomography.

Yakdiel Rodríguez-Gallo1, Rubén Orozco-Morales2, Marlen Pérez-Díaz3

  • 1Departamento de Electrónica y Telecomunicaciones, Universidad Central 'Marta Abreu' de Las Villas, Santa Clara, Cuba.

Physical and Engineering Sciences in Medicine
|March 24, 2021
PubMed
Summary

A new computed tomography (CT) method effectively reduces metal artifacts using CT slices alone. This image quality improvement helps preserve anatomical structures and aids medical diagnosis, showing promise for clinical integration.

Keywords:
Computed tomographyImage qualityImplantsMetal artifact reduction

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Area of Science:

  • Medical Imaging
  • Image Processing
  • Radiology

Background:

  • Metal artifacts in CT scans degrade image quality, potentially impacting medical diagnoses.
  • Existing metal artifact reduction (MAR) methods face challenges in effectively mitigating these artifacts.

Purpose of the Study:

  • To introduce a novel MAR method that corrects artifacts using only CT slices.
  • To evaluate the proposed method's efficacy in reducing artifacts and preserving image quality.

Main Methods:

  • Segmentation of metal implants using an entropy-based method.
  • Prior image generation via Gaussian filter, inpainting, and L0 Gradient Minimization (L0GM).
  • Sinogram correction through normalization/denormalization, followed by filtered back projection (FBP) and Nonlocal Means (NLM) filtering.

Main Results:

  • The proposed IMIF-MAR method demonstrated visible artifact reduction in both phantom and clinical datasets.
  • Quantitative analysis using five image quality metrics and ROI inspection confirmed artifact reduction.
  • The method effectively reduced streak artifacts and avoided new artifacts around implants.

Conclusions:

  • The IMIF-MAR method offers effective streak metal artifact reduction while preserving anatomical structures.
  • The algorithm improves the quality of clinical CT images affected by metal artifacts.
  • The proposed MAR approach shows potential for integration into clinical settings.