title: Computer-aided detection of breast cancers using Haar-like features in automated 3D breast ultrasound.
abstract: OBJECTIVE
  Automated 3D breast ultrasound (ABUS) has gained interest in breast imaging. Especially for screening women with dense breasts, ABUS appears to be beneficial. However, since the amount of data generated is large, the risk of oversight errors is substantial. Computer aided detection (CADe) may be used as a second reader to prevent oversight errors. When CADe is used in this fashion, it is essential that small cancers are detected, while the number of false positive findings should remain acceptable. In this work, the authors improve their previously developed CADe system in the initial candidate detection stage.
  
  
  METHODS
  The authors use a large number of 2D Haar-like features to differentiate lesion structures from false positives. Using a cascade of GentleBoost classifiers that combines these features, a likelihood score, highly specific for small cancers, can be efficiently computed. The likelihood scores are added to the previously developed voxel features to improve detection.
  
  
  RESULTS
  The method was tested in a dataset of 414 ABUS volumes with 211 cancers. Cancers had a mean size of 14.72 mm. Free-response receiver operating characteristic analysis was performed to evaluate the performance of the algorithm with and without using the aforementioned Haar-like feature likelihood scores. After the initial detection stage, the number of missed cancer was reduced by 18.8% after adding Haar-like feature likelihood scores.
  
  
  CONCLUSIONS
  The proposed technique significantly improves our previously developed CADe system in the initial candidate detection stage.
authors.affiliation: Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen 6525 GA, The Netherlands.
authors.forename: Tao
authors.initials: T
authors.lastname: Tan
authors.affiliation: Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen 6525 GA, The Netherlands.
authors.forename: Jan-Jurre
authors.initials: JJ
authors.lastname: Mordang
authors.affiliation: Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen 6525 GA, The Netherlands.
authors.forename: Jan
authors.initials: J
authors.lastname: van Zelst
authors.affiliation: Prevention and Screening Clinic, Jules Bordet, Brussel 1000, Belgium.
authors.forename: André
authors.initials: A
authors.lastname: Grivegnée
authors.affiliation: Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen 6525 GA, The Netherlands.
authors.forename: Albert
authors.initials: A
authors.lastname: Gubern-Mérida
authors.affiliation: Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen 6525 GA, The Netherlands.
authors.forename: Jaime
authors.initials: J
authors.lastname: Melendez
authors.affiliation: Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen 6525 GA, The Netherlands.
authors.forename: Ritse M
authors.initials: RM
authors.lastname: Mann
authors.affiliation: QView Medical, Inc, Los Altos, California 94022.
authors.forename: Wei
authors.initials: W
authors.lastname: Zhang
authors.affiliation: Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen 6525 GA, The Netherlands.
authors.forename: Bram
authors.initials: B
authors.lastname: Platel
authors.affiliation: Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen 6525 GA, The Netherlands.
authors.forename: Nico
authors.initials: N
authors.lastname: Karssemeijer
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D005188:False Negative Reactions; D005189:False Positive Reactions; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016013:Likelihood Functions; D010363:Pattern Recognition, Automated / Q000379:methods; D012372:ROC Curve; D012680:Sensitivity and Specificity; D013997:Time Factors; D016217:Ultrasonography, Mammary / Q000379:methods*