title: Computerized detection of masses in digitized mammograms using single-image segmentation and a multilayer topographic feature analysis.
abstract: OBJECTIVE
  We developed and evaluated a computer-aided detection (CAD) scheme for masses in digitized mammograms.
  
  
  METHODS
  A multistep CAD scheme was developed and tested. The method uses a technique of single-image segmentation with Gaussian bandpass filtering to yield a high sensitivity for mass detection. A rule-based multilayer topographic feature analysis method is then used to classify suspected regions. A set of 260 cases, including 162 verified masses, was divided into two subsets; one set was used to set the rule-based classification and one was used to test the performance of the scheme.
  
  
  RESULTS
  In a preliminary clinical study, the implemented detection scheme yielded 98% sensitivity with a false-positive detection rate of less than one false-positive region per image.
  
  
  CONCLUSIONS
  Single-image segmentation methods seem to have high sensitivity in selecting true-positive mass regions in the first stage of a CAD scheme. A multilayer topographic image feature analysis method in the second stage of a CAD scheme has the potential to significantly reduce the false-positive detection rate.
authors.affiliation: Department of Radiology, University of Pittsburgh, PA 15261-0001, USA.
authors.forename: B
authors.initials: B
authors.lastname: Zheng
authors.forename: Y H
authors.initials: YH
authors.lastname: Chang
authors.forename: D
authors.initials: D
authors.lastname: Gur
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D003936:Diagnosis, Computer-Assisted; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D008327:Mammography / Q000379:methods*; D012680:Sensitivity and Specificity