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

Linearizing mechanisms in conventional tomographic imaging.

S C Orphanoudakis, J W Strohbehn, C E Metz

    Medical Physics
    |January 1, 1978
    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

    An infrastructure for Integrated Electronic Health Record services: the role of XML (Extensible Markup Language).

    Journal of medical Internet research·2001
    Same author

    An open, component-based information infrastructure to support integrated regional healthcare networks.

    Studies in health technology and informatics·2001
    Same author

    Ideal observer approximation using Bayesian classification neural networks.

    IEEE transactions on medical imaging·2001
    Same author

    Components-of-variance models for random-effects ROC analysis: the case of unequal variance structures across modalities.

    Academic radiology·2001
    Same author

    Continuous versus categorical data for ROC analysis: some quantitative considerations.

    Academic radiology·2001
    Same author

    Computerized classification of benign and malignant masses on digitized mammograms: a study of robustness.

    Academic radiology·2000

    This study validates the linearity assumption in conventional tomography. It identifies mechanisms that effectively linearize the tomographic imaging process, crucial for accurate modulation transfer function analysis.

    Area of Science:

    • Medical Imaging
    • Physics
    • Image Processing

    Background:

    • Conventional tomography relies on the assumption of linearity for accurate image reconstruction.
    • Characterizing tomographic processes using modulation transfer functions necessitates this linearity assumption.

    Purpose of the Study:

    • To establish the validity of the linearity assumption in conventional tomography.
    • To identify the mechanisms responsible for the effective linearization of the tomographic process.

    Main Methods:

    • Fourier decomposition of the tomographic process.
    • Analysis of nonlinear contributions to integrated tomographic image intensity.

    Main Results:

    • The study confirms the validity of the linearity assumption in conventional tomography.

    Related Experiment Videos

  • Key mechanisms contributing to the effective linearization of the tomographic process were identified.

    • Conclusions:

    • The linearity assumption in conventional tomography is valid.
    • Understanding the linearization mechanisms is essential for accurate tomographic imaging and analysis.