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

Improving image contrast using principal component analysis for subsequent image segmentation.

Y Zhang1, A Goldszal, J Butman

  • 1Department of Diagnostic Radiology, Clinical Center, National Institutes of Health, Bethesda, MD 20892, USA.

Journal of Computer Assisted Tomography
|October 5, 2001
PubMed
Summary

This study introduces a novel method to enhance Magnetic Resonance (MR) image contrast by combining multiple images. Principal component analysis (PCA) is used to create composite MR images, improving segmentation accuracy.

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

Impact of Data Presentation on Physician Performance Utilizing Artificial Intelligence-Based Computer-Aided Diagnosis and Decision Support Systems.

Journal of digital imaging·2018
Same author

Changes in prostate cancer detection rate of MRI-TRUS fusion vs systematic biopsy over time: evidence of a learning curve.

Prostate cancer and prostatic diseases·2017
Same author

ANG1005 for breast cancer brain metastases: correlation between <sup>18</sup>F-FLT-PET after first cycle and MRI in response assessment.

Breast cancer research and treatment·2016
Same author

A phase II study of TRC105 in patients with hepatocellular carcinoma who have progressed on sorafenib.

United European gastroenterology journal·2015
Same author

Optimization of intrabone delivery of hematopoietic progenitor cells in a swine model using cell radiolabeling with [89]zirconium.

American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons·2015
Same author

Improving PET spatial resolution and detectability for prostate cancer imaging.

Physics in medicine and biology·2014

Area of Science:

  • Medical Imaging
  • Image Processing
  • Biomedical Engineering

Background:

  • Magnetic Resonance (MR) imaging is crucial for visualizing soft tissues.
  • Enhancing contrast in MR images is vital for accurate diagnosis and analysis.
  • Existing multispectral segmentation methods have limitations.

Purpose of the Study:

  • To develop a technique for improving MR image contrast.
  • To enable effective segmentation of enhanced MR images.
  • To reduce multispectral image sets for simplified analysis.

Main Methods:

  • Linear combination of multiple MR images with varying tissue contrast.
  • Derivation of weighting coefficients using Principal Component Analysis (PCA).
  • Segmentation of the contrast-enhanced composite image using 1D gray level-based methods.

Related Experiment Videos

Main Results:

  • Successfully generated contrast-enhanced composite MR images.
  • Demonstrated the reduction of multispectral image sets to composite eigenimages.
  • Enabled the application of 1D segmentation methods to multispectral data.

Conclusions:

  • The proposed technique effectively enhances MR image contrast.
  • PCA-based linear combination simplifies multispectral image analysis.
  • The method allows for robust segmentation using 1D techniques.