A two-stage method for lesion segmentation on digital mammograms

Yading Yuan, Mapyellen L. Giger, Kenji Suzuki, Hui Li, Andrew R. Jamieson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


In this paper, we present a two-stage method for the segmentation of breast mass lesions on digitized mammograms. A radial gradient index (RGI) based segmentation method is first used to estimate a initial contour close to the lesion boundary location in a computationally efficient manner. Then a region-based active contour algorithm, which minimizes an energy fucntion based on the homogeneities inside and outside of the envolving coutour, is applied to refine the contour closer to the lesion boundary. The minimization algorithm solves, by the level set method, the Euler-Lagrange equation that describes the contour evolution. By using a digitized screening film dababase with 96 biopy-proven, malignant lesions, we quantitatively compare this two-stage segmentation algorithm with a RGI-based method and a conventional region-growing algorithm by measuring the area similarity. At an overlap threshold of 0.30, the new method correctly segments 95% of the lesions while the prior methods delineate only 83% of the lesions. Our assessment demonstrates that the two-stage segmentation algorithm yields closer agreement with mannully contoured lesion boundaries.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2006
Subtitle of host publicationImage Processing
StatePublished - Jun 22 2006
Externally publishedYes
EventMedical Imaging 2006: Image Processing - San Diego, CA, United States
Duration: Feb 13 2006Feb 16 2006

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume6144 II
ISSN (Print)1605-7422


OtherMedical Imaging 2006: Image Processing
Country/TerritoryUnited States
CitySan Diego, CA


  • Computer-aided diagnosis
  • Level set
  • Mass lesion segmentation
  • Region-based active contour

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging


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