Computerized lesion detection on breast ultrasound

Karen Drukker, Maryellen L. Giger*, Karla Horsch, Matthew A. Kupinski, Carl J. Vyborny, Ellen B. Mendelson

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

186 Scopus citations


We investigated the use of a radial gradient index (RGI) filtering technique to automatically detect lesions on breast ultrasound. After initial RGI filtering, a sensitivity of 87% at 0.76 false-positive detections per image was obtained on a database of 400 patients (757 images). Next, lesion candidates were segmented from the background by maximizing an average radial gradient (ARD) index for regions grown from the detected points. At an overlap of 0.4 with a radiologist lesion outline, 75% of the lesions were correctly detected. Subsequently, round robin analysis was used to assess the quality of the classification of lesion candidates into actual lesions and false-positives by a Bayesian neural network. The round robin analysis yielded an Az value of 0.84, and an overall performance by case of 94% sensitivity at 0.48 false-positives per image. Use of computerized analysis of breast sonograms may ultimately facilitate the use of sonography in breast cancer screening programs.

Original languageEnglish (US)
Pages (from-to)1438-1446
Number of pages9
JournalMedical Physics
Issue number7
StatePublished - 2002


  • Breast sonography
  • Computer-aided diagnosis
  • Performance of lesion detection

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging


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