title: Computer-aided detection systems for breast masses: comparison of performances on full-field digital mammograms and digitized screen-film mammograms.
abstract: OBJECTIVE
  To compare the performance of computer aided detection (CAD) systems on pairs of full-field digital mammogram (FFDM) and screen-film mammogram (SFM) obtained from the same patients.
  
  
  METHODS
  Our CAD systems on both modalities have similar architectures that consist of five steps. For FFDMs, the input raw image is first log-transformed and enhanced by a multiresolution preprocessing scheme. For digitized SFMs, the input image is smoothed and subsampled to a pixel size of 100 microm x 100 microm. For both CAD systems, the mammogram after preprocessing undergoes a gradient field analysis followed by clustering-based region growing to identify suspicious breast structures. Each of these structures is refined in a local segmentation process. Morphologic and texture features are then extracted from each detected structure, and trained rule-based and linear discriminant analysis classifiers are used to differentiate masses from normal tissues. Two datasets, one with masses and the other without masses, were collected. The mass dataset contained 131 cases with 131 biopsy proven masses, of which 27 were malignant and 104 benign. The true locations of the masses were identified by an experienced Mammography Quality Standards Act (MQSA) radiologist. The no-mass data set contained 98 cases. The time interval between the FFDM and the corresponding SFM was 0 to 118 days.
  
  
  RESULTS
  Our CAD system achieved case-based sensitivities of 70%, 80%, and 90% at 0.9, 1.5, and 2.6 false positive (FP) marks/image, respectively, on FFDMs, and the same sensitivities at 1.0, 1.4, and 2.6 FP marks/image, respectively, on SFMs.
  
  
  CONCLUSIONS
  The difference in the performances of our FFDM and SFM CAD systems did not achieve statistical significance.
authors.affiliation: Department of Radiology, University of Michigan, Ann Arbor, MI 48109, USA. jvwei@umich.edu
authors.forename: Jun
authors.initials: J
authors.lastname: Wei
authors.forename: Lubomir M
authors.initials: LM
authors.lastname: Hadjiiski
authors.forename: Berkman
authors.initials: B
authors.lastname: Sahiner
authors.forename: Heang-Ping
authors.initials: HP
authors.lastname: Chan
authors.forename: Jun
authors.initials: J
authors.lastname: Ge
authors.forename: Marilyn A
authors.initials: MA
authors.lastname: Roubidoux
authors.forename: Mark A
authors.initials: MA
authors.lastname: Helvie
authors.forename: Chuan
authors.initials: C
authors.lastname: Zhou
authors.forename: Yi-Ta
authors.initials: YT
authors.lastname: Wu
authors.forename: Chintana
authors.initials: C
authors.lastname: Paramagul
authors.forename: Yiheng
authors.initials: Y
authors.lastname: Zhang
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001943:Breast Neoplasms / Q000175:diagnosis*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D003937:Diagnosis, Differential; D016002:Discriminant Analysis; D005189:False Positive Reactions; D005260:Female; D006801:Humans; D008327:Mammography / Q000379:methods*; D008875:Middle Aged; D012372:ROC Curve; D011856:Radiographic Image Enhancement / Q000379:methods*; D012680:Sensitivity and Specificity