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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.
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X-ray Imaging01:24

X-ray Imaging

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 X-rays, and by 1900, X-ray was widely...
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Phase-Contrast Microscopes
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Related Experiment Video

Updated: May 17, 2026

Cerenkov Luminescence Imaging of Interscapular Brown Adipose Tissue
06:28

Cerenkov Luminescence Imaging of Interscapular Brown Adipose Tissue

Published on: October 7, 2014

Dual-energy CT-based monochromatic imaging.

Lifeng Yu1, Shuai Leng, Cynthia H McCollough

  • 1Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA.

AJR. American Journal of Roentgenology
|October 26, 2012
PubMed
Summary
This summary is machine-generated.

Virtual monochromatic imaging from dual-energy CT offers improved image quality and artifact reduction. However, conventional single-energy CT may be preferable for routine scans without specific artifact correction needs.

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Area of Science:

  • Medical Imaging
  • Radiology
  • Computed Tomography

Background:

  • Dual-energy CT (DECT) provides spectral information beyond conventional single-energy CT.
  • Virtual monochromatic imaging (VMI) synthesizes images at various energy levels from DECT data.
  • VMI aims to enhance image quality and enable advanced applications.

Purpose of the Study:

  • To review methods for synthesizing VMI from DECT data.
  • To compare the quality of VMI with conventional single-energy CT (SECT).
  • To discuss clinical applications of DECT-based VMI.

Main Methods:

  • Synthesis of VMI using image-domain and projection-domain methods.
  • Comparison of VMI quality against SECT images at equivalent radiation doses.
  • Review of clinical use cases for VMI.

Main Results:

  • VMI can be synthesized effectively from DECT datasets.
  • VMI quality is comparable to or better than SECT under specific conditions.
  • DECT-based VMI demonstrates utility in artifact reduction and material differentiation.

Conclusions:

  • VMI from DECT can reduce beam-hardening artifacts and enable quantitative measurements.
  • VMI offers potential for contrast and noise optimization and metal artifact reduction.
  • For routine imaging without specific artifact correction needs, optimal SECT may suffice.