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 Experiment Videos

A segmentation-based method for metal artifact reduction.

Hengyong Yu1, Kai Zeng, Deepak K Bharkhada

  • 1Biomedical Imaging Division, VT-WFU School of Biomedical Engineering and Science, Virginia Technical, Blacksburg, VA 24061, USA. hengyongyu@vt.edu

Academic Radiology
|March 21, 2007
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Current State of Artificial Intelligence Adoption and Implementation in Neuroradiology Departments: Insights from a U.S. National Survey.

AJNR. American journal of neuroradiology·2026
Same author

ACR Appropriateness Criteria® Horner Syndrome.

Journal of the American College of Radiology : JACR·2025
Same author

ACR Appropriateness Criteria® Altered Mental Status, Coma, Delirium, and Psychosis: 2024 Update.

Journal of the American College of Radiology : JACR·2024
Same author

ACR Appropriateness Criteria® Imaging of Suspected Intracranial Hypotension.

Journal of the American College of Radiology : JACR·2024
Same author

ACR Appropriateness Criteria® Thoracic Back Pain.

Journal of the American College of Radiology : JACR·2024
Same author

Endolymphatic sac tumor mimicking an aneurysmal bone cyst.

Arquivos de neuro-psiquiatria·2024
Same journal

Improving Reliability of MRI Lumbar Spinal Stenosis Assessment Across Radiology and Spine Specialties: Impact of a Structured Education Intervention.

Academic radiology·2026
Same journal

Advances in CT and MRI for Yttrium-90 Radioembolization of Hepatocellular Carcinoma.

Academic radiology·2026
Same journal

Homogeneity of Liver Fat Distribution Serves as a Diagnostic Marker for Metabolic Dysfunction-Associated Steatohepatitis.

Academic radiology·2026
Same journal

MRI-based Predictors and Risk Constellations of Chronic Ankle Instability After Acute Lateral Ankle Sprain: A Multicenter Study.

Academic radiology·2026
Same journal

Early Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer using a Longitudinal US-based Stack-model.

Academic radiology·2026
Same journal

Evaluating the Impact of Embolization on Outcomes in Iliopsoas Hematomas: A Multicenter Retrospective Propensity-matched Study.

Academic radiology·2026
See all related articles

This study introduces an advanced segmentation-based interpolation method to significantly reduce metal artifacts from surgical clips in medical imaging. The new technique improves image quality by 20-40%, enhancing visualization of surrounding tissues.

Area of Science:

  • Medical imaging
  • Computer vision
  • Image processing

Background:

  • Surgical aneurysm clips cause significant metal artifacts in medical imaging.
  • Existing methods for artifact reduction have limitations.

Purpose of the Study:

  • To develop and evaluate a novel segmentation-based interpolation method for reducing metal artifacts caused by surgical aneurysm clips.

Main Methods:

  • A five-step process including coarse image reconstruction, metallic object segmentation using mean-shift, forward-projection, projection interpolation with a feedback strategy, and final image reconstruction.
  • Utilized physical phantom and real patient datasets for evaluation.

Main Results:

  • The proposed method reduced metal artifacts by 20-40% compared to previous state-of-the-art methods.

Related Experiment Videos

  • Improved visualization of soft tissues and osseous structures surrounding surgical clips.

    • Conclusions:

    • The mean-shift technique and feedback strategy effectively reduce metal artifacts.
    • The developed method enhances overall image quality for better diagnostic assessment.