Discover common properties of human observers' visual search and mathematical observers' scanning PART I: theory and conjecture

Xin He; Frank Samuelson; Rongping Zeng; Berkman Sahiner

doi:10.1117/12.2043318

11 March 2014 Discover common properties of human observers' visual search and mathematical observers' scanning PART I: theory and conjecture

Xin He, Frank Samuelson, Rongping Zeng, Berkman Sahiner

Author Affiliations +

Proceedings Volume 9037, Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment; 903712 (2014) https://doi.org/10.1117/12.2043318
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

Abstract

There is a lack of consensus in measuring observer performance in search tasks. To pursue a consensus, we set our goal as to obtain metrics that are practical, meaningful and objective. We consider a metric practical if it can be implemented to measure human and computer observers’ performance. To be meaningful, we propose to discover metrics that reflect the intrinsic properties of search observers. Thus, the meaningfulness of the metrics is ensured by the discovered properties being intrinsic. We set our success criteria as that the discovered properties can make verifiable predications. Thus the objectivity of the metrics is ensured by their prediction ability. The goal of this work is to present a theory and a conjecture toward two intrinsic properties of search observers: rationality in classification as measured by the location-known-exactly ROC curve and location uncertainty as measured by the effective set size. These two properties are used to develop search models in both single-response and free-response search tasks. To confirm whether these properties are “intrinsic”, in a companion paper, we investigate their ability in predicting search performance of both human and scanning channelized Hotelling observers.

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Xin He, Frank Samuelson, Rongping Zeng, and Berkman Sahiner "Discover common properties of human observers' visual search and mathematical observers' scanning PART I: theory and conjecture", Proc. SPIE 9037, Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment, 903712 (11 March 2014); https://doi.org/10.1117/12.2043318

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KEYWORDS

Lawrencium

Medical imaging

Visual process modeling

Electronic filtering

Image processing

Visualization

Data modeling

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