Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

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...
Electron Microscope Tomography and Single-particle Reconstruction01:07

Electron Microscope Tomography and Single-particle Reconstruction

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.
Electron Tomography
Electron tomography can be performed either in TEM or STEM (scanning transmission...
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...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Beech latewood density as a proxy for temperature reconstruction.

Science advances·2026
Same author

Biomimetic characterization by micro-computed tomography (μCT) of 3D hollow fibre membrane network bioreactors for tissue engineering.

Biomaterials science·2026
Same author

Wood you believe it-Detecting copper with hyperspectral imaging.

Waste management (New York, N.Y.)·2026
Same author

Predicting dialyzer fiber blocking is hard due to high intrapatient variability and limited utility of thrombin generation markers.

Scientific reports·2026
Same author

The Tervuren xylarium Wood Density Database (TWDD).

Scientific data·2026
Same author

Historical tree phenology data across contrasting sites in the Congo Basin.

Scientific data·2026

Related Experiment Video

Updated: May 13, 2026

Correlative Microscopy for 3D Structural Analysis of Dynamic Interactions
13:43

Correlative Microscopy for 3D Structural Analysis of Dynamic Interactions

Published on: June 24, 2013

Postprocessing method for reducing phase effects in reconstructed microcomputed-tomography data.

Erik L G Wernersson1, Matthieu N Boone, Jan Van den Bulcke

  • 1Centre for Image Analysis, Swedish University of Agricultural Sciences, Uppsala, Sweden. erikw@cb.uu.se

Journal of the Optical Society of America. A, Optics, Image Science, and Vision
|March 5, 2013
PubMed
Summary

This study introduces a new postprocessing method to remove refraction artifacts in x-ray computed tomography (CT) imaging. The technique offers faster parameter evaluation and works even without projection data, improving image quality.

More Related Videos

Using Synchrotron Radiation Microtomography to Investigate Multi-scale Three-dimensional Microelectronic Packages
08:46

Using Synchrotron Radiation Microtomography to Investigate Multi-scale Three-dimensional Microelectronic Packages

Published on: April 13, 2016

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

Related Experiment Videos

Last Updated: May 13, 2026

Correlative Microscopy for 3D Structural Analysis of Dynamic Interactions
13:43

Correlative Microscopy for 3D Structural Analysis of Dynamic Interactions

Published on: June 24, 2013

Using Synchrotron Radiation Microtomography to Investigate Multi-scale Three-dimensional Microelectronic Packages
08:46

Using Synchrotron Radiation Microtomography to Investigate Multi-scale Three-dimensional Microelectronic Packages

Published on: April 13, 2016

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

Area of Science:

  • Medical Imaging
  • Computational Physics
  • Image Processing

Background:

  • X-ray computed tomography (CT) resolution improvements lead to increased signal from refraction.
  • Refraction artifacts in CT images can degrade image quality and require removal.
  • Existing methods for artifact removal are often projection-based (preprocessing).

Purpose of the Study:

  • To propose a novel postprocessing method for removing refraction artifacts in CT images.
  • To offer an alternative to preprocessing phase-retrieval or phase-removal algorithms.
  • To demonstrate comparable image quality to state-of-the-art methods.

Main Methods:

  • A postprocessing method based on deconvolution is proposed.
  • The method removes artifacts after conventional CT reconstruction.
  • Parameter evaluation is performed for speed and efficiency.

Main Results:

  • The proposed postprocessing method effectively removes refraction artifacts.
  • Parameter evaluation is significantly faster than existing methods.
  • The method achieves image quality comparable to state-of-the-art techniques.

Conclusions:

  • The deconvolution-based postprocessing method is an effective way to remove refraction artifacts in CT.
  • This approach offers advantages in speed and applicability, especially when projection data is unavailable.
  • The method provides a viable alternative for enhancing CT image quality.