Paper
26 June 2001 Analysis of computer-aided diagnosis on radiologists' performance using an independent database
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Abstract
We developed a computerized method for the automated classification of benign and malignant mammographic mass lesions. An independent evaluation of the automatic method on a database consisting of 110 cases showed that the classification method is robust to variations in case-mix and in film digitization technique. We also evaluated the effectiveness of the method as an aid to radiologists in differentiating between benign and malignant masses. A total of 6 mammographers and 6 community general radiologists participated in an observer study. In that study, the radiologists interpreted the 110 cases in the independent database, unknown to both the radiologist observers and the trained computer classification method, first without and then with the computer aid. Results from our observer study indicated that use of the computer aid improved the abilities for both the expert and general radiologists in the task of differentiating between benign and malignant mammographic mass lesions, as indicated by the increase in Az values and sensitivities at statistically significant levels. With the database we used, however, we were unable to demonstrate the effect of computer aid on radiologist performance regarding the number of benign cases sent for biopsy. In this study, we investigate the relationship between the value of the computer output and the effect on the observers in terms of changing their patient management decision upon viewing the computer output.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhimin Huo, Maryellen Lissak Giger, and Carl J. Vyborny "Analysis of computer-aided diagnosis on radiologists' performance using an independent database", Proc. SPIE 4324, Medical Imaging 2001: Image Perception and Performance, (26 June 2001); https://doi.org/10.1117/12.431197
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Cited by 2 scholarly publications.
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KEYWORDS
Databases

Biopsy

Mammography

Statistical analysis

Breast cancer

Computer aided diagnosis and therapy

Biological research

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