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 Video

Updated: Jun 10, 2026

Clinical Imaging of Microwave Mammography
05:28

Clinical Imaging of Microwave Mammography

Published on: November 14, 2025

Malignancy detection in digital mammograms: important reader characteristics and required case numbers.

Warren M Reed1, Warwick B Lee, Jennifer N Cawson

  • 1Medical Radiation Sciences, Faculty of Health Sciences, The University of Sydney, Cumberland Campus, East Street, PO Box 170, Lidcombe NSW 1825, Australia. warren.reed@sydney.edu.au

Academic Radiology
|August 20, 2010
PubMed
Summary

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

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

Radiation Risk in 2D Mammography Screening: A Scoping Review of Modelling Strategies and Emerging AI Applications.

Journal of medical radiation sciences·2025

Reader performance in mammography improves with more experience and higher case volumes. Increased years of certification, experience, and weekly reading hours correlate with better diagnostic accuracy (Az values).

Area of Science:

  • Radiology
  • Medical Imaging
  • Diagnostic Performance

Background:

  • Reader performance in mammography interpretation is crucial for early cancer detection.
  • Factors influencing reader performance, such as experience and practice volume, require further investigation.

Purpose of the Study:

  • To investigate the relationship between reader performance metrics and practice-related factors in mammography.
  • To identify key indicators of reader experience and practice that correlate with diagnostic accuracy.

Main Methods:

  • Sixty-nine readers evaluated 50 mammography cases (15 abnormal, 35 normal).
  • Performance was assessed using receiver operating characteristic (ROC) curve analysis (Az values), sensitivity, and specificity.
  • Statistical analyses (Spearman correlation, Mann-Whitney test) compared performance to years of certification, experience, and case volume.

More Related Videos

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
15:48

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Published on: December 15, 2014

Related Experiment Videos

Last Updated: Jun 10, 2026

Clinical Imaging of Microwave Mammography
05:28

Clinical Imaging of Microwave Mammography

Published on: November 14, 2025

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
15:48

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Published on: December 15, 2014

Main Results:

  • Higher Az values were significantly associated with more years of certification (P = .004), years of experience (P = .0001), and weekly reading hours (P = .003).
  • Readers interpreting ≥5000 cases/year (P = .03) or 2000-4999 cases/year (P = .05) showed significantly higher Az values than those reading <1000 cases/year.
  • Reader experience and practice volume demonstrably impact diagnostic performance.

Conclusions:

  • Mammographic reader performance varies significantly with practice parameters like experience and case volume.
  • Findings suggest potential benchmarks for diagnostic efficacy that could inform policy and practice.
  • Establishing optimal practice levels is essential for ensuring high-quality mammographic interpretation.