title: Assessment of a novel mass detection algorithm in mammograms.
abstract: BACKGROUND
  Mammography is the most effective procedure for an early detection of the breast abnormalities. Masses are a type of abnormality, which are very difficult to be visually detected on mammograms.
  
  
  OBJECTIVE
  In this paper an efficient method for detection of masses in mammograms is implemented.
  
  
  METHODS
  The proposed mass detector consists of two major steps. In the first step, several suspicious regions are extracted from the mammograms using an adaptive thresholding technique. In the second step, false positives originating by the previous stage are reduced by a machine learning approach.
  
  
  METHODS
  All modules of the mass detector were assessed on mini-MIAS database. In addition, the algorithm was tested on INBreast database for more validation.
  
  
  RESULTS
  According to FROC analysis, our mass detection algorithm outperforms other competing methods.
  
  
  CONCLUSIONS
  We should not just insist on sensitivity in the segmentation phase because if we forgot FP rate, and our goal was just higher sensitivity, then the learning algorithm would be biased more toward false positives and the sensitivity would decrease dramatically in the false positive reduction phase. Therefore, we should consider the mass detection problem as a cost sensitive problem because misclassification costs are not the same in this type of problems.
authors: Department of Computer Engineering, Iran University of Science and Technology (IUST), Tehran, Iran.
authors: Ehsan
authors: E
authors: Kozegar
authors: Mohsen
authors: M
authors: Soryani
authors: Behrouz
authors: B
authors: Minaei
authors: Inês
authors: I
authors: Domingues
mesh_terms: D000465:Algorithms; D001940:Breast / Q000002:abnormalities / Q000473:pathology; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000000981:diagnostic imaging*; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D055088:Early Detection of Cancer; D005260:Female; D006801:Humans; D008327:Mammography / Q000379:methods*; D008403:Mass Screening; D011856:Radiographic Image Enhancement / Q000379:methods*