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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.
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...
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

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...
Positron Emission Tomography01:29

Positron Emission Tomography

Positron emission tomography (PET) is a medical imaging technique involving radiopharmaceuticals — substances that emit short-lived radiation. Although the first PET scanner was introduced in 1961, it took 15 more years before radiopharmaceuticals were combined with the technique and revolutionized its potential.
One of the main requirements of a PET scan is a positron-emitting radioisotope, which is produced in a cyclotron and then attached to a substance used by the part of the body being...

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Related Experiment Video

Updated: Jun 24, 2026

Construction of a Preclinical Multimodality Phantom Using Tissue-mimicking Materials for Quality Assurance in Tumor Size Measurement
06:33

Construction of a Preclinical Multimodality Phantom Using Tissue-mimicking Materials for Quality Assurance in Tumor Size Measurement

Published on: July 29, 2013

A low-cost density reference phantom for computed tomography.

Zachary H Levine1, Mingdong Li, Anthony P Reeves

  • 1Photon Physics Group, National Institute for Standards and Technology, Gaithersburg, Maryland 20899-8410, USA. zlevine@nist.gov

Medical Physics
|March 19, 2009
PubMed
Summary
This summary is machine-generated.

A novel foam material may serve as a density reference standard for lung tissue imaging. This polyurethane and polyisocyanurate foam could enhance the systematic diagnosis of lung diseases using imaging techniques.

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Last Updated: Jun 24, 2026

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Area of Science:

  • Materials Science
  • Medical Imaging
  • Biomedical Engineering

Background:

  • Accurate density measurement is crucial for medical imaging, particularly in diagnosing lung diseases.
  • Current methods for density calibration in medical imaging may lack precision in specific ranges.
  • Polyurethane and polyisocyanurate foams offer tunable physical properties relevant for calibration standards.

Purpose of the Study:

  • To evaluate a commercially available polyurethane and polyisocyanurate foam as a potential density reference standard.
  • To determine the suitability of the foam for calibrating imaging systems in the density range of lung tissue.
  • To explore the implications of using such a foam for improving the systematic diagnosis of lung diseases.

Main Methods:

  • Characterization of a commercial foam composed of polyurethane and polyisocyanurate.
  • Density measurement of the foam using Hounsfield units.
  • Comparison of the foam's density range with that of human lung tissue.

Main Results:

  • The foam was characterized and found to possess a density below -400 Hounsfield units.
  • This density range is coincident with the typical density of lung tissue.
  • The foam exhibits potential as a reliable density reference standard for lung imaging.

Conclusions:

  • The evaluated foam is suitable for use as a density reference standard, particularly for lung tissue imaging.
  • This foam could contribute to more systematic and accurate diagnosis of lung diseases.
  • Further research may validate its application in clinical settings for enhanced diagnostic accuracy.