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Related Concept Videos

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...
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...

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Related Experiment Video

Updated: Jun 10, 2026

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography
07:01

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography

Published on: October 24, 2019

Improved tomographic reconstructions using adaptive time-dependent intensity normalization.

Valeriy Titarenko1, Sofya Titarenko, Philip J Withers

  • 1Henry Moseley X-ray Imaging Facility, School of Materials, University of Manchester, Grosvenor Street, Manchester M13 9PL, UK. valeriy.titarenko@manchester.ac.uk

Journal of Synchrotron Radiation
|August 21, 2010
PubMed
Summary
This summary is machine-generated.

A new adaptive technique corrects artifacts in synchrotron micro-tomography by modeling time-dependent background variations. This method significantly reduces ring and wave artifacts in 3D reconstructions, improving image quality.

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Area of Science:

  • * X-ray computed tomography
  • * Image processing and artifact reduction

Background:

  • * Synchrotron-based micro-tomography requires normalization using a white field image.
  • * Time-dependent variations in illumination and detector sensitivity cause the white field to differ from the projection background.
  • * Standard normalization methods introduce ring and wave artifacts into 3D reconstructions.

Purpose of the Study:

  • * To introduce a novel adaptive technique for normalizing micro-tomography projection images.
  • * To account for time-dependent variations in illumination and detection sensitivity.
  • * To suppress ring and wave artifacts in 3D reconstructions.

Main Methods:

  • * Modeling the background as a product of two time-dependent terms: illumination and detection.
  • * Representing illumination as a scaled and shifted function along a fixed direction.
  • * Representing detection as a function translated by an unknown 2D vector.

Main Results:

  • * The adaptive technique successfully normalized projection images, producing cleaner data.
  • * Significant reductions in ring and wave artifacts were observed in applied datasets.
  • * Demonstrated effectiveness on Salix variegata stem and Danio rerio zebrafish samples.

Conclusions:

  • * The proposed adaptive method effectively corrects for time-dependent background variations in micro-tomography.
  • * It offers a robust solution for suppressing ring and wave artifacts.
  • * The technique has potential applicability to other tomographic imaging geometries, including laboratory X-ray computed tomography.