title: Computer-aided mammographic screening for spiculated lesions.
abstract: OBJECTIVE
  To study the use of a computer vision method as a second reader for the detection of spiculated lesions on screening mammograms.
  
  
  METHODS
  An algorithmic computer process for the detection of spiculated lesions on digitized screen-film mammograms was applied to 85 four-view clinical cases: 36 cases with cancer proved by means of biopsy and 49 cases with negative findings at examination and follow-up. The computer detections were printed as film with added outlines that indicated the suspected cancers. Four radiologists screened the 85 cases twice, once without and once with the computer reports as ancillary films.
  
  
  RESULTS
  The algorithm alone achieved 100% sensitivity, with a specificity of 82%. The computer reports increased the average radiologist sensitivity by 9.7% (P = .005), moving from 80.6% to 90.3%, with no decrease in average specificity.
  
  
  CONCLUSIONS
  The study demonstrated that computer analysis of mammograms can provide a substantial and statistically significant increase in radiologist screening efficacy.
authors.affiliation: Sandia National Laboratories, Livermore, Calif.
authors.forename: W P
authors.initials: WP
authors.lastname: Kegelmeyer
authors.forename: J M
authors.initials: JM
authors.lastname: Pruneda
authors.forename: P D
authors.initials: PD
authors.lastname: Bourland
authors.forename: A
authors.initials: A
authors.lastname: Hillis
authors.forename: M W
authors.initials: MW
authors.lastname: Riggs
authors.forename: M L
authors.initials: ML
authors.lastname: Nipper
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000453:epidemiology; D003663:Decision Trees; D005260:Female; D006801:Humans; D008327:Mammography; D011856:Radiographic Image Enhancement; D011857:Radiographic Image Interpretation, Computer-Assisted; D012189:Retrospective Studies; D012680:Sensitivity and Specificity