Computer-aided diagnosis of lesions on multi-modality images of the breast

Maryellen L. Giger, Zhimin Huo, Karla Horsch, Edward R. Hendrick, Luz A. Venta, Carl J. Vyborny, Ioana R. Bonta, L. Lan

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


We have developed computerized methods for the analysis of lesions that combine results from different imaging modalities, in this case digitized mammograms and sonograms of the breast, for distinguishing between malignant and benign lesions. The computerized classification method - applied here to mass lesions seen on both digitized mammograms and sonograms, includes: (1) automatic lesion extraction, (2) automated feature extraction, and (3) automatic classification. The results for both modalities are then merged into an estimate of the likelihood of malignancy. For the mammograms, computer-extracted lesion features include degree of spiculation, margin sharpness, lesion density, and lesion texture. For the ultrasound images, lesion features include margin definition, texture, shape, and posterior acoustic attenuation. Malignant and benign lesions are better distinguished when features from both mammograms and ultrasound images are combined.

Original languageEnglish (US)
Pages (from-to)656-660
Number of pages5
JournalProceedings of SPIE - The International Society for Optical Engineering
Issue number2
StatePublished - 2001


  • Breast imaging
  • Computer-aided diagnosis
  • Digital mammography
  • Ultrasound

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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