Visual-search (VS) model observers have the potential to provide reliable predictions of human-observer performance in detection-localization tasks. The purpose of this work was to examine some characteristics of human gaze on breast images with the goal of informing the design of our VS observers. Using a helmet-mounted eye- tracking system, we recording the movement of gaze from human observers as they searched for masses in sets of 2D digital breast tomosynthesis (DBT) images. The masses in this study were of a single profile. The DBT images were extracted from image volumes reconstructed with filtered back-projection and penalized maximum- likelihood methods. Fixation times associated with observer points of interest (POIs) were computed from the observer data. The fixation times were then compared to sets of morphological feature values extracted from the images. These features, extracted as cross-correlations involving the mass profile and the test image, included the matched filter (MF), gradient MF, and Laplacian MF. For this initial investigation, we computed correlation coefficients between the fixation times and the feature values.