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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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German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with...
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Cardiac computed tomography (CT) scanning is an advanced cardiac imaging technique that utilizes CT technology, with or without intravenous (IV) contrast, to produce accurate cross-sectional virtual slices of specific areas of the heart, coronary circulation, and major blood vessels such as the aorta, pulmonary veins, and arteries. The computer processes these slices to generate three-dimensional images. Multidetector CT (MDCT) is a rapid form of CT scanning that captures multiple slices...
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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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Imaging Studies I: CT and MRI01:14

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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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Dual-energy CT imaging with limited-angular-range data.

Buxin Chen1, Zheng Zhang1, Dan Xia1

  • 1Department of Radiology, The University of Chicago, Chicago, IL 60637, United States of America.

Physics in Medicine and Biology
|July 28, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a new directional-total-variation (DTV) algorithm for dual-energy computed tomography (DECT) using limited-angular range (LAR) data. The DTV algorithm significantly reduces artifacts, enabling accurate image reconstruction and quantitative analysis comparable to full-angular range DECT.

Keywords:
atomic numberdirectional-total-variationdual-energy CTiodine cocentrationlimited-angular-range reconstruction

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Area of Science:

  • Medical Imaging
  • Computed Tomography
  • Image Reconstruction

Background:

  • Dual-energy computed tomography (DECT) typically uses full-angular range (FAR) data (360°).
  • Interest is growing in DECT with limited-angular range (LAR) data (≤180°), but image reconstruction methods for LAR DECT are underexplored.
  • Artifacts are a common issue in image reconstruction from LAR DECT data.

Purpose of the Study:

  • To investigate image reconstruction in DECT using limited-angular range (LAR) data.
  • To minimize artifacts in DECT images reconstructed from low- and high-kVp data acquired over LARs (≤180°).
  • To evaluate the effectiveness of a directional-total-variation (DTV) algorithm for LAR DECT image reconstruction.

Main Methods:

  • Image reconstruction from LAR data was formulated as a convex optimization problem.
  • The problem involved minimizing data L2-norm with constraints on the image's directional total variation (DTV) along orthogonal axes.
  • A DTV algorithm was applied to solve the optimization problem, with numerical studies conducted using data from 14° to 180° arcs.

Main Results:

  • Monochromatic images reconstructed using the DTV algorithm from LAR data exhibited substantially reduced artifacts compared to existing algorithms.
  • The improved image quality facilitated accurate estimation of physical quantities, including effective atomic number and iodine contrast concentration.
  • Quantitative and visual analyses confirmed the effectiveness of the DTV algorithm for LAR DECT.

Conclusions:

  • LAR DECT, when reconstructed with the DTV algorithm, can yield monochromatic images comparable to those obtained from FAR DECT.
  • Quantitative estimation of physical quantities from LAR DECT data is feasible and accurate using this method.
  • The findings suggest potential for designing practical LAR DECT scanning configurations.