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Proceedings Paper

Effects of the continuous and discrete confidence rating scales in ROC observer studies
Author(s): Lubomir M. Hadjiiski; Heang-Ping Chan; Berkman Sahiner; Mark A. Helvie; Marilyn A. Roubidoux
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Paper Abstract

We previously conducted an observer study evaluating radiologists' performance for characterization of mammographic masses on serial mammograms with and without CAD. 253 temporal image pairs (138 malignant and 115 benign) from 96 patients containing masses on serial mammograms were used. The interval change characteristics of the masses on each temporal pair were analyzed by our CAD program to differentiate malignant and benign masses. The classifier achieved a test Az value of 0.87 for the data set. Eight MQSA radiologists and 2 fellows assessed the temporal masses and provided estimates of the likelihood of malignancy (LM) and BI-RADS assessment without and then with CAD. The LM estimates were provided on a quasi-continuous confidence-rating scale (CRS) of 1 to 100. In the current study we investigated the effects of using discrete CRS with fewer categories on ROC analysis. We simulated three discrete CRSs containing 5, 10, and 20 categories by binning the radiologists’ LM quasi-continuous ratings. For the ten radiologists, without CAD, the average Az in estimating the LM for the 5, 10, 20 and 100 category CRSs were 0.788, 0.786, 0.785, and 0.787, respectively. With CAD, the observers' Az improved to 0.845, 0.843, 0.844, and 0.843, respectively. The improvement was statistically significant (p<0.011) for each CRS. The partial area index for the four CRSs without CAD was 0.198, 0.204, 0.200, and 0.206, respectively. With CAD the partial area index was also significantly improved to 0.369, 0.365, 0.369, and 0.366, respectively (p<0.006 for all CRSs). The use of continuous and discrete confidence-rating scales in this study had minimal effect on the analysis of observer performance.

Paper Details

Date Published: 6 April 2005
PDF: 7 pages
Proc. SPIE 5749, Medical Imaging 2005: Image Perception, Observer Performance, and Technology Assessment, (6 April 2005); doi: 10.1117/12.595725
Show Author Affiliations
Lubomir M. Hadjiiski, Univ. of Michigan (United States)
Heang-Ping Chan, Univ. of Michigan (United States)
Berkman Sahiner, Univ. of Michigan (United States)
Mark A. Helvie, Univ. of Michigan (United States)
Marilyn A. Roubidoux, Univ. of Michigan (United States)


Published in SPIE Proceedings Vol. 5749:
Medical Imaging 2005: Image Perception, Observer Performance, and Technology Assessment
Miguel P. Eckstein; Yulei Jiang, Editor(s)

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