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

Statistical profiles in computed tomography

R A Kramer, B M Yoshikawa, P O Scheibe

    Radiology
    |October 1, 1977
    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

    Ecosystem change and human health: implementation economics and policy.

    Philosophical transactions of the Royal Society of London. Series B, Biological sciences·2017
    Same author

    Correlation of pharmacokinetics with the antitumor activity of Cetuximab in nude mice bearing the GEO human colon carcinoma xenograft.

    Cancer chemotherapy and pharmacology·2005
    Same author

    Inhibition of angiogenesis and metastasis in two murine models by the matrix metalloproteinase inhibitor, BMS-275291.

    Cancer research·2001
    Same author

    Preclinical antitumor activity of BMS-214662, a highly apoptotic and novel farnesyltransferase inhibitor.

    Cancer research·2001
    Same author

    Identification of essential acidic residues of outer membrane protease OmpT supports a novel active site.

    FEBS letters·2001
    Same author

    Crystal structure of the outer membrane protease OmpT from Escherichia coli suggests a novel catalytic site.

    The EMBO journal·2001
    Same journal

    Erratum for: Prediction of Lobar Emphysema Progression with a CT-Based Foundational Model.

    Radiology·2026
    Same journal

    Erratum for: Associations of MRI-derived Paraspinal IMAT and LMM with Cardiometabolic Risk Factors: Results from a German Cohort.

    Radiology·2026
    Same journal

    Erratum for: Blue Rubber Bleb Nevus Syndrome.

    Radiology·2026
    Same journal

    Redefining the Clinical Role of MRI in Endometrial Cancer Staging.

    Radiology·2026
    Same journal

    To Ablate or Not to Ablate: The Colorectal Liver Metastasis Question.

    Radiology·2026
    Same journal

    The Limits of Radiologic Categorization in Pulmonary Nonsolid Nodules.

    Radiology·2026
    See all related articles

    A new diagnostic console uses statistical parameters from CT scans to better analyze tissue characteristics. This advanced analysis aids in differentiating between various brain lesions with similar appearances.

    Area of Science:

    • Medical imaging
    • Radiology
    • Neurology

    Background:

    • Current diagnostic consoles offer limited characterization of computed tomography (CT) scan data.
    • Distinguishing between certain brain lesions with similar imaging appearances can be challenging.

    Purpose of the Study:

    • To develop and evaluate a diagnostic console capable of deriving advanced statistical parameters from CT scans.
    • To enhance the characterization of CT numbers within regions of interest.
    • To improve the differentiation of specific brain lesions.

    Main Methods:

    • A diagnostic console integrating a high-resolution video display and microcomputer was programmed.
    • The system was designed to derive a battery of statistical parameters from selected areas on CT scans.

    Related Experiment Videos

  • These parameters were used to analyze and compare CT number distributions.
  • Main Results:

    • The console successfully derived comprehensive statistical parameters from CT scan regions of interest.
    • These parameters provided a more meaningful characterization of CT numbers compared to existing methods.
    • A combination of statistical parameters demonstrated the ability to discriminate between lesions like porencephalic cysts, epidermoid tumors, and cystic gliomas.

    Conclusions:

    • The developed diagnostic console offers improved capabilities for quantitative analysis of CT scans.
    • Enhanced statistical parameter derivation facilitates more accurate differentiation of challenging brain lesions.
    • This technology has the potential to improve diagnostic accuracy in neuroradiology.