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Proceedings Paper

Using incomplete and imprecise localization data on images to improve estimates of detection accuracy
Author(s): Richard G. Swensson; Glenn S. Maitz; Jill L. King; David Gur
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Paper Abstract

We tested new analytic procedures for combining an observer's image-ratings of lesion-likelihood with localization reports that are incomplete (unavailable on images rated as 'normal') and/or imprecise (possibly scored as 'correct' by chance), and for fitting a constrained ROC formulation to the rating data alone. Eight radiologist readers in a previous study had rated the likelihood of nodular lesions on each of 250 chest-film cases (39 with subtle nodules, 36 with 'typical' nodules and 175 normal cases) that were presented in two display modes (original films or on video workstation). Ratings in the four positive categories (2 to 5) were accompanied by reports that grossly localized the suspected nodules into one of 7 film- regions (upper, middle or lower portions of left or right lung field, or retrocardiac), but there was no localization for the cases rated as 'normal' (category 1). In each of 29 sets of data, we estimated the area below the ROC curve (Az) and its standard error using three different fits: (1) the usual ROC formulation, (2) the constrained ROC formulation and (3) the new procedure that included incomplete and imprecise localization data (I&I). Estimates of Az from the usual and constrained ROC fits were quite similar unless the standard ROC exhibited an upward 'hook,' but standard errors of Az were always the same or smaller for the constrained ROC fit. The I&I fit that included localization data often estimated Az to be either larger or smaller than the usual or constrained ROC fits that considered only the rating data, but its Az had substantially smaller standard errors in 28 of the 29 sets of observer data.

Paper Details

Date Published: 24 May 1999
PDF: 8 pages
Proc. SPIE 3663, Medical Imaging 1999: Image Perception and Performance, (24 May 1999); doi: 10.1117/12.349665
Show Author Affiliations
Richard G. Swensson, Univ. of Pittsburgh School of Medicine (United States)
Glenn S. Maitz, Univ. of Pittsburgh School of Medicine (United States)
Jill L. King, Univ. of Pittsburgh School of Medicine (United States)
David Gur, Univ. of Pittsburgh School of Medicine (United States)


Published in SPIE Proceedings Vol. 3663:
Medical Imaging 1999: Image Perception and Performance
Elizabeth A. Krupinski, Editor(s)

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