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Proceedings Paper • Open Access

Presentation of similar images for diagnosis of breast masses on mammograms: analysis of the effect on residents

Paper Abstract

We have been developing a computerized scheme for selecting visually similar images that would be useful to radiologists in the diagnosis of masses on mammograms. Based on the results of the observer performance study, the presentation of similar images was useful, especially for less experienced observers. The test cases included 50 benign and 50 malignant masses. Ten observers, including five breast radiologists and five residents, were asked to provide the confidence level of the lesions being malignant before and after the presentation of similar images. By use of multireader, multi-case receiver operating characteristic analysis, the average areas under the curves for the five residents were 0.880 and 0.896 without and with similar images, respectively (p=0.040). There were four malignant cases in which the initial ratings were relatively low, but the similar images alerted the residents to increase their confidence levels of malignancy close to those by the breast radiologists. The presentation of similar images may cause some observers falsely to increase their suspicion for some benign cases; however, if similar images can alert radiologists to recognize the signs of malignancy and also help them to decrease their suspicion correctly for some benign cases, they can be useful in the diagnosis on mammograms.

Paper Details

Date Published: 3 March 2009
PDF: 8 pages
Proc. SPIE 7260, Medical Imaging 2009: Computer-Aided Diagnosis, 72600R (3 March 2009); doi: 10.1117/12.811447
Show Author Affiliations
Chisako Muramatsu, The Univ. of Chicago (United States)
Gifu Univ. (Japan)
Robert A. Schmidt, The Univ. of Chicago (United States)
Junji Shiraishi, The Univ. of Chicago (United States)
Qiang Li, Duke Univ. (United States)
Hiroshi Fujita, Gifu Univ. (Japan)
Kunio Doi, The Univ. of Chicago (United States)


Published in SPIE Proceedings Vol. 7260:
Medical Imaging 2009: Computer-Aided Diagnosis
Nico Karssemeijer; Maryellen L. Giger, Editor(s)

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