Automated segmentation of digitized mammograms

Acad Radiol. 1995 Jan;2(1):1-9. doi: 10.1016/s1076-6332(05)80239-9.


Rationale and objectives: Fast and reliable segmentation of digital mammograms into breast and nonbreast regions is an important prerequisite for further image analysis. We are developing a segmentation algorithm that is fully automated and can operate independent of type of digitizing system, image orientation, and image projection.

Methods: The algorithm identifies unexposed and direct-exposure image regions and generates a border surrounding the valid breast region, which can then be used as input for further image analysis. The program was tested on 740 digitized mammograms; the segmentation results were evaluated by two expert mammographers and two medical physicists.

Results: In 97% of the mammograms, the segmentation results were rated as acceptable for use in computer-aided diagnostic schemes. Segmentation problems encountered in the remaining 22 images (2.9%) were most often caused by digitization artifacts or poor mammographic technique.

Conclusion: The developed algorithm can serve as a component of an "intelligent" workstation for computer-aided diagnosis in mammography.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Algorithms*
  • Artifacts
  • Breast Neoplasms / diagnostic imaging*
  • Chi-Square Distribution
  • Diagnosis, Computer-Assisted*
  • Female
  • Humans
  • Image Processing, Computer-Assisted*
  • Mammography*
  • Radiographic Image Enhancement