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Model observers for image classification, usually rely on either knowing the statistics for the two classes or being able to estimate them. This is a reasonable assumption when designing simple experiments for object detection or localization, but it does not transfer well to more complex problems. In this paper, we show a new methodology for task based image quality assessment based on a two alternative forced choice comparison with an ensemble of classes characterizing the normal class (𝐻0 ), without the need to fully describe the abnormal class (𝐻1)
Francesc Massanes andA. Hans Vija
"Class classification using two alternate force choice against an ensemble of normal examples", Proc. SPIE 11599, Medical Imaging 2021: Image Perception, Observer Performance, and Technology Assessment, 115990Z (15 February 2021); https://doi.org/10.1117/12.2582119
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Francesc Massanes, A. Hans Vija, "Class classification using two alternate force choice against an ensemble of normal examples," Proc. SPIE 11599, Medical Imaging 2021: Image Perception, Observer Performance, and Technology Assessment, 115990Z (15 February 2021); https://doi.org/10.1117/12.2582119