UC Santa Barbara

In the field of oncology, three-dimensional volumetric medical images provide radiologists with a detailed visual representation of various anatomical structures that facilitate the early detection and characterization of malignant lesions but at the cost of an increased search space. Recent work (Lago et al., 2021) establishes that human observers rely heavily on peripheral visual processing away from the point of fixation when searching for signals in 3D volumetric images. The searcher’s over-reliance on peripheral vision interacts strongly with how much of the volume they explore and with how much they report they have explored. Specifically, observers under-explore—as determined by the percentage of the volume covered by the Useful Field of View (UFOV)—and overestimate the percentage of volume they explored through self-report measures. Consequently, they miss small signals during the search. This thesis aims to elucidate the psychological factors mediating human under-exploration of 3D volumetric image data. The second thrust of this thesis is to investigate three solutions to mitigate the detrimental impact of under-exploration in 3D images. The first method is a 2D synthetic view of the 3D data that observers can utilize as additional information when performing the 3D search. I establish through behavioral measurements and a computational model simulating foveated vision how the 2D-S guides eye movements to suspicious regions in the 3D volume. In turn, this guidance allows observers to find the small signal that would otherwise be missed without the 2D-S adjunct. The second method involves a different type of search aid, a convolutional neural network, which acts as a computer-aided detection system to assist human observers during the 3D search. Like the 2D-S, it guides eye movements to suspicious regions in a 3D volumetric image that observers would have otherwise not looked at. The last method is inspired by the power of group decision-making. It investigates how combining multiple independent judgments from a group of searchers can lead to more exploration of the search space and a higher chance of detecting the small signal. Together, the body of work herein provides empirical results from laboratory studies to further our understanding of how humans interact with 3D imaging modalities with the goal of improving healthcare services relating to early cancer screenings.