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 Concept Videos

Effects of EDTA on End-Point Detection Methods01:18

Effects of EDTA on End-Point Detection Methods

Different methods, such as visual observance of metal-ion indicators, spectroscopic techniques, and potentiometric methods, can determine the endpoint of an EDTA titration.
In the visual method, metal-ion indicators (metallochromic dyes), which have distinct colors in their free and complex forms, are added to the mixture to signal the titration's end point. They form stable complexes with metal ions, but these complexes are weaker than the corresponding metal–EDTA complexes. As a result, EDTA...
Ultrasonography01:17

Ultrasonography

Ultrasonography is an imaging technique that uses high-frequency sound waves to visualize the body's internal structures. It is a non-invasive and safe procedure that does not involve the use of ionizing radiation, making it widely used in various medical fields. Ultrasonography is used to study heart function, blood flow in the neck or extremities, certain conditions such as gallbladder disease, and fetal growth and development.
During an ultrasonography procedure, a handheld device called a...

You might also read

Related Articles

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

Sort by
Same author

A novel deep learning-based grading system for assessing breast arterial calcification on mammograms, as an independent risk factor for predicting adverse cardiovascular events.

La Radiologia medica·2026
Same author

Amplifying image quality gain in x-ray phase contrast imaging of mastectomy samples with deep learning denoising.

Physics in medicine and biology·2026
Same author

Semi-Supervised Deep Learning-Based Model for Segmentation of Breast Arterial Calcification on Screening Mammograms.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes·2025
Same author

Factors associated with junior doctor plain trauma X-ray interpretation accuracy and strategies for improvement: a scoping review.

BMC medical imaging·2025
Same author

Accuracy of junior doctor plain trauma X-ray interpretation: a systematic review and meta-analysis.

BMC medical imaging·2025
Same author

e-Learning in Radiological Image Interpretation for Medical Students: A Systematic Review.

Academic radiology·2025
Same journal

An Intentional and Ethical Integration of AI in Medical Imaging.

Radiologic technology·2026
Same journal

Benefits of Integrating AI Into Computer-Aided Detection Systems.

Radiologic technology·2026
Same journal

Using Artificial Intelligence to Enhance Analysis of Chest Computed Tomography.

Radiologic technology·2026
Same journal

A Practice-Aligned Approach to Integrating AI in Radiation Sciences Education.

Radiologic technology·2026
Same journal

Site Visitors: The Unsung Heroes of the Accreditation Process.

Radiologic technology·2026
Same journal

Extended Reality Innovations in Medical Imaging Education.

Radiologic technology·2026
See all related articles

Related Experiment Video

Updated: May 7, 2026

Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly
12:50

Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly

Published on: April 14, 2014

E-tutorial improves students' ability to detect lesions.

BaoLin Pauline Soh, Warren Michael Reed, Ann Poulos

    Radiologic Technology
    |September 14, 2013
    PubMed
    Summary
    This summary is machine-generated.

    A brief e-learning tutorial significantly improved breast lesion detection in first-year medical radiation sciences (MRS) students. Eye-tracking data revealed enhanced viewing patterns and faster lesion identification after the educational intervention.

    More Related Videos

    Erosion Identification in Metacarpophalangeal Joints in Rheumatoid Arthritis using High-Resolution Peripheral Quantitative Computed Tomography
    06:31

    Erosion Identification in Metacarpophalangeal Joints in Rheumatoid Arthritis using High-Resolution Peripheral Quantitative Computed Tomography

    Published on: October 6, 2023

    Related Experiment Videos

    Last Updated: May 7, 2026

    Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly
    12:50

    Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly

    Published on: April 14, 2014

    Erosion Identification in Metacarpophalangeal Joints in Rheumatoid Arthritis using High-Resolution Peripheral Quantitative Computed Tomography
    06:31

    Erosion Identification in Metacarpophalangeal Joints in Rheumatoid Arthritis using High-Resolution Peripheral Quantitative Computed Tomography

    Published on: October 6, 2023

    Area of Science:

    • Medical Imaging and Radiation Sciences
    • Educational Technology in Healthcare
    • Radiologic Perception and Cognitive Neuroscience

    Background:

    • First-year medical radiation sciences (MRS) students require effective training for accurate lesion detection.
    • Understanding the impact of educational interventions on early-stage technologists' visual search patterns is crucial.
    • Eye-tracking metrics offer objective insights into the learning process during image interpretation.

    Purpose of the Study:

    • To evaluate the effectiveness of an e-learning tutorial on breast lesion detection in first-year MRS students.
    • To analyze changes in eye-tracking metrics and diagnostic performance before and after the intervention.
    • To explore the relationship between educational input and visual search strategies in novice radiographers.

    Main Methods:

    • Fourteen first-year MRS students were randomly assigned to an experimental or control group.
    • The experimental group completed an e-learning tutorial on breast lesion detection.
    • Participants performed two image-detection sessions using mammographic images, with performance analyzed via Receiver Operating Characteristic (ROC) methodology.

    Main Results:

    • The experimental group showed a 45% increase in fixations and a 30% increase in sensitivity (P=.022) post-tutorial.
    • Lesion detection improved significantly in the experimental group, with a 49% decrease in mean time to first fixation on the lesion (P=.016).
    • Changes in eye position metrics and error analysis correlated with improved lesion identification.

    Conclusions:

    • A brief e-learning tutorial can enhance breast lesion detection skills in novice MRS students.
    • The study suggests early-level visual processing changes may occur following targeted educational interventions.
    • Findings provide insights into radiologic perception and cognitive neuroscience for improving technologist training.