Salience measure for assessing scale-based features in mammograms.
This work assesses the usefulness of an objective, task-based image quality measure that is correlated with perceived image quality; the measure uses the most salient features contained within a medical image. Contributions include the development of a perceptually correlated metric that is useful for quantifying the salience of local, low-level visual cues and identifying those spatial frequencies that are most distinct and perhaps most relied upon by radiologists for decision making. A set of 40 mammograms and registered eye position data from nine observers was used to evaluate the salience metric. A parsimonious analysis-of-variance model explained the variance in the salience results. This analysis is generalized to a population of readers and cases. An analysis of salience versus time of first eye fixation shows good correlation with true positive lesions that were found by experienced readers in less than 2 s.
US Army, Night Vision and Electronic Sensors Directorate, Fort Belvoir, Virginia 22060, USA. philip.perconti@us.army.mil
Philip
P
Perconti
Murray H
MH
Loew
D000704:Analysis of Variance; D003463:Cues; D003662:Decision Theory; D004056:Differential Threshold; D006801:Humans; D016014:Linear Models; D008327:Mammography / Q000379:methods* / Q000706:statistics & numerical data; D015588:Observer Variation; D012016:Reference Values; D017603:Signal Detection, Psychological; D013382:Subtraction Technique; D013647:Task Performance and Analysis; D014796:Visual Perception; D014894:Weights and Measures