Proceedings of the Annual Meeting of the Cognitive Science Society

Radiologists can discriminate between normal and abnormalbreast tissue at a glance, suggesting that radiologists might beusing some “global signal” of abnormality. Our study inves-tigated whether texture descriptions can be used to character-ize the global signal of abnormality and whether radiologistsuse this information during interpretation. Synthetic imageswere generated using a texture synthesis algorithm trained ontexture descriptions extracted from sections of mammograms.Radiologists completed a task that required rating the abnor-mality of briefly presented tissue sections. When the abnormaltissue had no visible lesion, radiologists seemed to use texturedescriptions; performance was similar across real and synthe-sized tissue sections. However, when the abnormal tissue had avisible lesion, radiologists seemed to rely on additional mech-anisms beyond the texture descriptions; performance increasedfor the real tissue sections. These findings suggest that radiol-ogists can use texture descriptions as global signals of abnor-mality in interpretation of breast tissue.