title: Fragmentary window filtering for multiscale lung nodule detection: preliminary study.
abstract: OBJECTIVE
  The authors evaluated computer-assisted diagnostic (CAD) methods used to detect suspicious areas on lung radiographs.
  
  
  METHODS
  The authors designed a fragmentary window filtering (FWF) algorithm for detecting lung nodule patterns, which generally appear as circular areas of high opacity on the chest radiograph. The FWF algorithm helps differentiate circular patterns from overlapping radiographic background. A multiscale analysis was performed to locate multiscale nodules. Receiver operating characteristic analysis was performed by using a lung nodule that was extracted from a chest radiograph. The nodule underwent scalings and subsequent superimposition onto 140 normal regions of interest from six chest radiographs.
  
  
  RESULTS
  The FWF method was superior to the matched filtering method in the detection of suspicious areas.
  
  
  CONCLUSIONS
  The proposed FWF-based method should provide improved detection of lung nodules on chest radiographs.
authors.affiliation: Department of Radiology, College of Medicine, University of South Florida, Tampa 33612-4799, USA.
authors.forename: F
authors.initials: F
authors.lastname: Mao
authors.forename: W
authors.initials: W
authors.lastname: Qian
authors.forename: J
authors.initials: J
authors.lastname: Gaviria
authors.forename: L P
authors.initials: LP
authors.lastname: Clarke
mesh_terms: D000465:Algorithms; D003936:Diagnosis, Computer-Assisted; D005189:False Positive Reactions; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008171:Lung Diseases / Q000175:diagnosis*; D011857:Radiographic Image Interpretation, Computer-Assisted; D013902:Radiography, Thoracic / Q000379:methods; D012680:Sensitivity and Specificity