Fulltext:
87548.pdf
Embargo:
until further notice
Size:
244.3Kb
Format:
PDF
Description:
Publisher’s version
Publication year
2010Source
European Radiology, 20, 10, (2010), pp. 2323-30ISSN
Annotation
01 oktober 2010
Publication type
Article / Letter to editor
Display more detailsDisplay less details
Organization
Radiology
Journal title
European Radiology
Volume
vol. 20
Issue
iss. 10
Page start
p. 2323
Page end
p. 30
Subject
ONCOL 5: Aetiology, screening and detection; Medical Imaging - Radboud University Medical CenterAbstract
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.
This item appears in the following Collection(s)
- Academic publications [246164]
- Electronic publications [133742]
- Faculty of Medical Sciences [93268]
Upload full text
Use your RU credentials (u/z-number and password) to log in with SURFconext to upload a file for processing by the repository team.