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Mammography Reading with Computer-Aided Detection (CAD): Single View vs Two Views

  • Olorunsola F. Agbaje
  • Susan M. Astley
  • Maureen G. C. Gillan
  • Caroline R. M. Boggis
  • Mary Wilson
  • Nicky B. Barr
  • Ursula M. Beetles
  • Miriam A. Griffiths
  • Anil Jain
  • Jill Johnson
  • Rita M. Roberts
  • Heather Deans
  • Karen Duncan
  • Geeta Iyengar
  • Pamela M. Griffiths
  • Magnus A. McGee
  • Stephen W. Duffy
  • Fiona J. Gilbert
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4046)

Abstract

Two-view mammography is known to be more effective than one-view in increasing breast cancer detection and reducing recall rates. In addition, there is evidence that computer aided detection (CAD) systems are able to prompt malignant abnormalities that have been overlooked by a human reader. Using data from the UK NHS Breast Screening Programme (NHSBSP) we compared double reading with single reading using a CAD system, to assess the relationship between CAD and number of views in terms of the sensitivity of the screening regime to cancer detection and the recall rate of normal cases. CAD appeared to contribute to an increased cancer detection rate with single-view mammography without significantly increasing the recall rate. For two-view mammography, there was no significant change in sensitivity using CAD but a significantly higher recall rate. However, single-view mammography was used in incident rounds in which previous mammograms were available whereas two-view mammography was used in the prevalent round where no previous mammograms were available.

Keywords

Recall Rate Cancer Detection Rate Double Reading High Recall Rate Prior Mammogram 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Olorunsola F. Agbaje
    • 1
  • Susan M. Astley
    • 2
  • Maureen G. C. Gillan
    • 3
  • Caroline R. M. Boggis
    • 4
  • Mary Wilson
    • 4
  • Nicky B. Barr
    • 4
  • Ursula M. Beetles
    • 4
  • Miriam A. Griffiths
    • 4
  • Anil Jain
    • 4
  • Jill Johnson
    • 4
  • Rita M. Roberts
    • 4
  • Heather Deans
    • 5
  • Karen Duncan
    • 5
  • Geeta Iyengar
    • 5
  • Pamela M. Griffiths
    • 2
  • Magnus A. McGee
    • 6
  • Stephen W. Duffy
    • 1
  • Fiona J. Gilbert
    • 3
  1. 1.Department of EpidemiologyMathematics & Statistics, Wolfson Institute of Preventive MedicineLondonUK
  2. 2.Department of Imaging Science & Biomedical EngineeringUniversity of ManchesterManchesterUK
  3. 3.Department of RadiologyUniversity of AberdeenUK
  4. 4.Nightingale CentreWithington HospitalManchesterUK
  5. 5.NE Scotland Breast Screening CentreAberdeenUK
  6. 6.Department of Public Health & General PracticeChristchurch School of MedicineNZ

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