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

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

1.3K
When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
1.3K

You might also read

Related Articles

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

Sort by
Same author

Mapping the Structures of Adverse Childhood Experiences: A Network Analysis and a Sex-Differentiated Structural Framework for Prevention and Intervention.

Journal of interpersonal violence·2026
Same author

Do adverse childhood experiences intensify the impact of hazardous drinking on depression? Application of quantile regression analysis.

Child abuse & neglect·2026
Same author

Early postnatal changes in thyroid-stimulating hormone and subsequent neurodevelopment in preterm infants.

Frontiers in endocrinology·2026
Same author

Cross-resistance-guided phage cocktail design for effective mitigation of necrotic enteritis in poultry.

Microbiological research·2026
Same author

Effective transfer of tumor annotations from hematoxylin and eosin to fluorescence images of breast and lung tissues.

Journal of biomedical optics·2025
Same author

Breast Cancer Classification in Deep Ultraviolet Fluorescence Images Using a Patch-Level Vision Transformer Framework.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025

Related Experiment Video

Updated: May 4, 2026

Human Brown Adipose Tissue Depots Automatically Segmented by Positron Emission Tomography/Computed Tomography and Registered Magnetic Resonance Images
09:21

Human Brown Adipose Tissue Depots Automatically Segmented by Positron Emission Tomography/Computed Tomography and Registered Magnetic Resonance Images

Published on: February 18, 2015

12.3K

Material decomposition-based improved normalized metal artifact reduction method (MD-NMAR) in photon counting CT.

Jeonghyeon Nam1, Joonbeom Kim1, Dong Hye Ye2

  • 1Department of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology, Daegu 42988, Republic of Korea.

Physics in Medicine and Biology
|August 8, 2025
PubMed
Summary
This summary is machine-generated.

Photon counting computed tomography (PCCT) offers enhanced imaging. A new material decomposition method significantly reduces metal artifacts in PCCT scans, improving image quality in both simulations and experiments.

Keywords:
material decompositionnormalized metal artifact reductionphoton counting CTvirtual monochromatic image

More Related Videos

Protocol for the Evaluation of MRI Artifacts Caused by Metal Implants to Assess the Suitability of Implants and the Vulnerability of Pulse Sequences
08:19

Protocol for the Evaluation of MRI Artifacts Caused by Metal Implants to Assess the Suitability of Implants and the Vulnerability of Pulse Sequences

Published on: May 17, 2018

9.9K
Neutron Radiography and Computed Tomography of Biological Systems at the Oak Ridge National Laboratory's High Flux Isotope Reactor
10:24

Neutron Radiography and Computed Tomography of Biological Systems at the Oak Ridge National Laboratory's High Flux Isotope Reactor

Published on: May 7, 2021

2.4K

Related Experiment Videos

Last Updated: May 4, 2026

Human Brown Adipose Tissue Depots Automatically Segmented by Positron Emission Tomography/Computed Tomography and Registered Magnetic Resonance Images
09:21

Human Brown Adipose Tissue Depots Automatically Segmented by Positron Emission Tomography/Computed Tomography and Registered Magnetic Resonance Images

Published on: February 18, 2015

12.3K
Protocol for the Evaluation of MRI Artifacts Caused by Metal Implants to Assess the Suitability of Implants and the Vulnerability of Pulse Sequences
08:19

Protocol for the Evaluation of MRI Artifacts Caused by Metal Implants to Assess the Suitability of Implants and the Vulnerability of Pulse Sequences

Published on: May 17, 2018

9.9K
Neutron Radiography and Computed Tomography of Biological Systems at the Oak Ridge National Laboratory's High Flux Isotope Reactor
10:24

Neutron Radiography and Computed Tomography of Biological Systems at the Oak Ridge National Laboratory's High Flux Isotope Reactor

Published on: May 7, 2021

2.4K

Area of Science:

  • Medical Imaging
  • Radiology
  • Image Processing

Background:

  • Photon counting computed tomography (PCCT) provides superior spatial and spectral information compared to conventional CT.
  • Metal artifacts pose a significant challenge in CT imaging, hindering accurate diagnosis.
  • Existing metal artifact reduction (MAR) methods have limitations in PCCT.

Purpose of the Study:

  • To develop and evaluate a novel material decomposition-based method for reducing metal artifacts in PCCT.
  • To leverage the unique spectral information from PCCT for improved artifact correction.
  • To enhance the accuracy and diagnostic utility of PCCT imaging in the presence of metallic implants.

Main Methods:

  • Utilized normalized MAR (NMAR) with calibration data to generate initial basis material images.
  • Applied NMAR for soft tissue correction and least squares fitting with virtual monochromatic images (VMIs) for hard tissue correction.
  • Reverted artifact-reduced material images to bin-wise images for iterative refinement using NMAR.

Main Results:

  • The proposed method demonstrated significant reduction in metal artifacts in PCCT images.
  • Achieved an average reduction of 6.3% in root mean squared error in dual-energy simulations.
  • Showcased noticeable improvements in table-top PCCT experiments compared to conventional NMAR.

Conclusions:

  • Material decomposition offers a promising approach for effective metal artifact reduction in PCCT.
  • The developed method enhances image quality and diagnostic potential of PCCT.
  • This technique holds potential for clinical applications involving metallic materials in CT scans.