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

Local computed tomography via iterative deblurring

G Wang1, D L Snyder, M W Vannier

  • 1Mallinckrodt Institute of Radiology, Washington University, Saint Louis, MO 63110, USA. gwang@brian.wustl.edu

Scanning
|November 1, 1996
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

Deblurring subject to nonnegativity constraints when known functions are present with application to object-constrained computerized tomography.

IEEE transactions on medical imaging·2001
Same author

Developmental toxicity interactions of methanol and radiofrequency radiation or 2-methoxyethanol in rats.

International journal of toxicology·2001
Same author

Effect of aging on the negative chronotropic and anti-beta-adrenergic actions of adenosine in the rat heart.

Journal of cardiovascular pharmacology·1999
Same author

Accelerated solvent extraction and gas chromatography/mass spectrometry for determination of polycyclic aromatic hydrocarbons in smoked food samples.

Journal of agricultural and food chemistry·1999
Same author

Development of a 96-well enzyme-linked solid-phase assay for beta-glucanase and xylanase.

Journal of agricultural and food chemistry·1999
Same author

KGF and FGF-10 stimulate liquid secretion in human fetal lung.

Pediatric research·1999
Same journal

Retracted: Diagnostic Efficacy of CT Radiomic Features in Pulmonary Invasive Mucinous Adenocarcinoma.

Scanning·2023
Same journal

Retracted: 3D Convolutional Neural Network Framework with Deep Learning for Nuclear Medicine.

Scanning·2023
Same journal

Retracted: Observation on the Effect of MRI Image Scanning on Knee Pain in Football Injury.

Scanning·2023
Same journal

Retracted: Optimal Cellular Microscopic Pattern Recognizer- (OCMPR-) Based Wireless Detection Network for Efficiently Leveraging the Parallel Distributed Processing Capabilities.

Scanning·2023
Same journal

Retracted: Changes of Volume Parameters in the Treatment of Graves Ophthalmopathy by Endoscopic Transethmoidal Decompression of the Orbital Inner Wall Combined with Fat Decompression.

Scanning·2023
Same journal

Retracted: Diagnostic Value of Specialist Systems in Sports Knee Injuries.

Scanning·2023
See all related articles

This study introduces an iterative deblurring method for localized X-ray computed tomography reconstruction. The technique shows feasibility in simulations, offering advantages for imaging specific regions of interest.

Area of Science:

  • Medical Imaging
  • Computational Imaging
  • Image Reconstruction

Background:

  • X-ray computed tomography (CT) is a fundamental imaging technique.
  • Current CT reconstruction methods can be computationally intensive and may reconstruct entire volumes.
  • Targeted reconstruction of specific regions is desirable for efficiency and dose reduction.

Purpose of the Study:

  • To adapt an iterative deblurring method for localized CT reconstruction.
  • To apply this method to both parallel-beam and cone-beam CT geometries.
  • To evaluate the method's performance using simulated projection data.

Main Methods:

  • An iterative deblurring algorithm was modified for localized image reconstruction.
  • The method was designed to utilize only projection data from the region of interest (ROI).

Related Experiment Videos

  • Numerical simulations were performed using both noise-free and noisy projection data.

    • Main Results:

    • The feasibility of the iterative deblurring method for localized CT reconstruction was demonstrated.
    • Successful reconstruction was achieved with both noise-free and noisy simulated projection data.
    • The method theoretically preserves nonnegativity and ensures monotonic convergence.

    Conclusions:

    • The adapted iterative deblurring method provides a viable approach for localized CT reconstruction.
    • This technique offers potential benefits for targeted imaging applications in X-ray computed tomography.
    • The method's theoretical properties suggest robustness and reliability in image reconstruction.