Using computer-aided detection in mammography as a decision support.
Objective: To evaluate an interactive computer-aided detection (CAD) system for reading mammograms to improve decision making.Methods: A dedicated mammographic workstation has been developed in which readers can probe image locations for the presence of CAD information. If present, CAD findings are...
| Publicado en: | European Radiology Vol. 20; no. 10; pp. 2323 - 2331 |
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| Autores principales: | , , , , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Oct2010
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104924010&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104924010 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09387994 NPH jtl: European Radiology issn: 09387994 maglogo: N pubinfo: dt: Oct2010 vid: 20 iid: 10 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104924010 53703847 NLM20532890 2010796858 10.1007/s00330-010-1821-8 NLM20532890 PMC2940044 104924010 ppf: 2323 ppct: 8 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Using computer-aided detection in mammography as a decision support. aug: au: Samulski M Hupse R Boetes C Mus RD den Heeten GJ Karssemeijer N Samulski, Maurice Hupse, Rianne Boetes, Carla Mus, Roel D M den Heeten, Gerard J Karssemeijer, Nico affil: Department of Radiology, Radboud University Nijmegen Medical Centre, Geert Grooteplein 10, 6500 HB, Nijmegen, The Netherlands sug: subj: Breast Neoplasms Diagnosis Breast Neoplasms Pathology Mammography Methods Computers and Computerization Decision Support Techniques Early Detection of Cancer False Positive Results Human Image Processing, Computer Assisted Oncology Methods Observer Bias Specialties, Medical Methods Sensitivity and Specificity Software Time Factors User-Computer Interface ab: Objective: To evaluate an interactive computer-aided detection (CAD) system for reading mammograms to improve decision making.Methods: A dedicated mammographic workstation has been developed in which readers can probe image locations for the presence of CAD information. If present, CAD findings are displayed with the computed malignancy rating. A reader study was conducted in which four screening radiologists and five non-radiologists participated to study the effect of this system on detection performance. The participants read 120 cases of which 40 cases had a malignant mass that was missed at the original screening. The readers read each mammogram both with and without CAD in separate sessions. Each reader reported localized findings and assigned a malignancy score per finding. Mean sensitivity was computed in an interval of false-positive fractions less than 10%.Results: Mean sensitivity was 25.1% in the sessions without CAD and 34.8% in the CAD-assisted sessions. The increase in detection performance was significant (p = 0.012). Average reading time was 84.7 ± 61.5 s/case in the unaided sessions and was not significantly higher when interactive CAD was used (85.9 ± 57.8 s/case).Conclusion: Interactive use of CAD in mammography may be more effective than traditional CAD for improving mass detection without affecting reading time. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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