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

Mammographic databases.

R M Nishikawa1

  • 1Department of Radiology, MC-2026, The University of Chicago, 5841 S. Maryland Ave., Chicago, IL 60637, USA. r-nishikawa@uchicago.edu

Breast Disease
|February 3, 2005
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

Using breast radiographers' reports as a second opinion for radiologists' readings of microcalcifications in digital mammography.

The British journal of radiology·2014
Same author

Validation of a power-law noise model for simulating small-scale breast tissue.

Physics in medicine and biology·2013
Same author

Scanning translucent glass-ceramic x-ray storage phosphors.

Proceedings of SPIE--the International Society for Optical Engineering·2012
Same author

Automated detection of mass lesions in dedicated breast CT: a preliminary study.

Medical physics·2012
Same author

On the orientation of mammographic structure.

Medical physics·2011
Same author

Task-based assessment of breast tomosynthesis: effect of acquisition parameters and quantum noise.

Medical physics·2010
Same journal

Paget disease of the breast: An often-overlooked malignancy.

Breast disease·2026
Same journal

Retrospective analysis of survival of patients with HER2-positive breast cancer with microscopic residual invasive disease after neoadjuvant chemotherapy.

Breast disease·2025
Same journal

Association between AKT1 polymorphisms and susceptibility to breast cancer in the Iranian population.

Breast disease·2025
Same journal

Circulating tumor cells as a clinical, diagnostic, and prognostic biomarker in breast cancer.

Breast disease·2025
Same journal

Isolated breast myeloid sarcoma: A diagnostic and therapeutic challenge. A case report and literature review.

Breast disease·2025
Same journal

Imaging evaluation of nipple discharge: Review of literature and management considerations.

Breast disease·2025
See all related articles

Large digital mammogram databases are essential for training medical residents and advancing automated computer analysis. This review outlines ideal database requirements, image specifications, and current/planned large-scale mammography collections.

Area of Science:

  • Radiology
  • Medical Imaging
  • Computer Science

Background:

  • Large mammographic databases are crucial for resident education and developing automated computer analysis of mammograms.
  • A unified collection of digital mammograms promotes educational consistency and enables robust comparisons of various computerized techniques.
  • While current efforts utilize digitized mammograms, future databases will incorporate full-field digital mammograms.

Purpose of the Study:

  • To review the essential requirements for creating comprehensive mammographic databases.
  • To describe the characteristics of existing and planned large-scale mammography databases.
  • To define the image specifications and organizational needs for an ideal mammographic database.

Main Methods:

  • Literature review of existing mammographic databases.

Related Experiment Videos

  • Analysis of requirements for image quality, such as spatial resolution.
  • Examination of database organization, size, and content for ideal mammography collections.

    • Main Results:

    • Several small mammographic databases currently exist.
    • Multiple large-scale databases (≥1,000 cases) are under development.
    • Key requirements for image data and database structure have been identified.

    Conclusions:

    • Standardized, large-scale digital mammography databases are necessary for advancing medical education and computer-aided diagnosis.
    • The development and organization of these databases require careful consideration of image properties and content.
    • Ongoing development of large databases will significantly impact future research and clinical applications in mammography.