Three scenarios of ranking inconsistencies involving search tasks

Xin He; Frank W. Samuelson; Rongping Zeng; Berkman Sahiner

doi:10.1117/12.2217617

24 March 2016 Three scenarios of ranking inconsistencies involving search tasks

Xin He, Frank W. Samuelson, Rongping Zeng, Berkman Sahiner

Proceedings Volume 9787, Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment; 97870U (2016) https://doi.org/10.1117/12.2217617
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

Abstract

Our previous work on assessment of digital breast tomosynthesis (DBT) image quality revealed inconsistencies in ranking the reconstruction algorithms’ performances for a location-known-exactly (LKE) detection and a location-unknown searching task. Such results made us wonder that ranking inconsistencies may not be rare phenomena at all. In this work, we conducted a small literature review that involved three publications (He, Samuelson, Zeng and Sahiner SPIE 2016; Park, Kupinski, Clarkson and Barrett, IPMI 2003 and JOSA 2005). These publications compared the LKE and search performance for a variety of observers using the AUC value as the performance criterion (human observers, CHOs for detection, scanning CHOs for search, and the Markov Chain Monte Carlo ideal observer for detection and search). We categorized the experimental findings into three types of ranking inconsistencies: 1) Ranking inconsistencies in LKE and search tasks; 2) human/ideal observer ranking inconsistencies; and 3) LKE/search ranking inconsistencies in the presence of signal variability. The empirical evidence presented in this work suggested that ranking inconsistencies for imaging systems existed, but these inconsistencies often do not draw enough attention in the literature.

Citation Download Citation

Xin He, Frank W. Samuelson, Rongping Zeng, and Berkman Sahiner "Three scenarios of ranking inconsistencies involving search tasks", Proc. SPIE 9787, Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment, 97870U (24 March 2016); https://doi.org/10.1117/12.2217617

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