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Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
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INbreast: toward a full-field digital mammographic database.

Inês C Moreira1, Igor Amaral, Inês Domingues

  • 1Faculdade de Medicina, Alameda Prof. Hernâni Monteiro, Universidade do Porto, Portugal. icm@estsp.ipp.pt

Academic Radiology
|November 15, 2011
PubMed
Summary

A new mammographic database, INbreast, has been developed to aid in breast cancer detection research. This comprehensive dataset includes full-field digital mammograms with expert annotations, offering a valuable resource for advancing computer-aided diagnosis systems.

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Area of Science:

  • Medical Imaging
  • Radiology
  • Computer-Aided Diagnosis

Background:

  • Computer-aided detection and diagnosis (CAD) systems assist radiologists in identifying breast lesions.
  • Existing mammographic databases often lack comprehensive features for research.
  • There is a need for high-quality datasets to develop and validate breast imaging algorithms.

Purpose of the Study:

  • To introduce and describe the INbreast mammographic database.
  • To provide a valuable resource for research in breast cancer detection and diagnosis.
  • To support the development of advanced computer-aided diagnosis systems.

Main Methods:

  • Acquisition of full-field digital mammograms using Siemens MammoNovation technology.
  • Inclusion of 115 cases (410 images) with diverse breast conditions.

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Last Updated: May 27, 2026

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  • Annotation of lesions (masses, calcifications, asymmetries, distortions) by specialists with contours provided in XML format.

    • Main Results:

    • The INbreast database comprises 410 full-field digital mammograms.
    • Cases include women with bilateral disease and mastectomy patients.
    • Precise lesion annotations are available for research purposes.

    Conclusions:

    • The INbreast database offers a unique resource with full-field digital mammograms and expert annotations.
    • Its wide variability of cases and public availability make it a valuable reference.
    • This database is expected to advance research in breast cancer imaging and CAD systems.