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Computed Tomography01:10

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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.
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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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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.
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Introduction: MRI and CT scans are crucial advancements in medical imaging techniques, playing a vital role in diagnosing conditions related to the gastrointestinal (GI) system. Each scan serves distinct purposes, targets specific areas, and requires unique nursing duties.
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Evaluation of a commercial Model Based Iterative reconstruction algorithm in computed tomography.

Nicoletta Paruccini1, Raffaele Villa2, Claudia Pasquali1

  • 1Medical Physics Department, ASST Monza, Italy.

Physica Medica : PM : an International Journal Devoted to the Applications of Physics to Medicine and Biology : Official Journal of the Italian Association of Biomedical Physics (AIFB)
|June 7, 2017
PubMed
Summary
This summary is machine-generated.

Model Based Iterative Reconstruction (IMR) significantly enhances CT image quality, improving spatial resolution and low contrast detectability while reducing noise. This advanced algorithm allows for substantial patient dose reduction without compromising diagnostic performance.

Keywords:
Computed tomographyModel Based Iterative reconstruction algorithm

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Area of Science:

  • Medical Imaging
  • Radiology
  • Image Processing

Background:

  • Iterative reconstruction algorithms are increasingly used in clinical CT scans.
  • These algorithms aim to reduce radiation dose while maintaining diagnostic image quality.

Purpose of the Study:

  • To evaluate a commercial Model Based Iterative Metal Artifact Reduction (IMR) algorithm.
  • The study assessed patient dose and image quality using standard and alternative metrics.

Main Methods:

  • Phantoms (Catphan, density, water) were scanned with varying CTDIvol and reconstruction thickness.
  • Images were reconstructed using Filtered Back Projection (FBP), statistical iDose, and Model Based IMR.
  • Image quality was assessed using Modulation Transfer Function (MTF), Target Transfer Function (TTF), noise analysis (Standard Deviation, Noise Power Spectrum), and Low Contrast Detectability (LCD).

Main Results:

  • Model Based IMR improved MTF by 12-64% and TTF for high-density objects.
  • Noise was reduced by 44-66%, with altered noise power spectrum behavior.
  • LCD improved by 35-45%, suggesting a potential 50% CTDIvol reduction.
  • Actual dose reduction of 25-35% was confirmed via CTDIvol median values.

Conclusions:

  • Model Based IMR offers significant improvements in CT image quality.
  • The algorithm effectively reduces patient radiation dose.