Where Do Experts Look While Doing 3D Image Segmentation

Published in Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research \\& Applications, 2016

3D image segmentation is a fundamental process in many scientific and medical applications. Automatic algorithms do exist, but there are many use cases where these algorithms fail. The gold standard is still manual segmentation or review. Unfortunately, even for an expert this is laborious, time consuming, and prone to errors. Existing 3D segmentation tools do not currently take into account human mental models and low-level perception tasks. Our goal is to improve the quality and efficiency of manual segmentation and review by analyzing how experts perform segmentation. As a preliminary step we conducted a field study with 8 segmentation experts, recording video and eye tracking data. We developed a novel coding scheme to analyze this data and verified that it successfully covers and quantifies the low-level actions, tasks and behaviors of experts during 3D image segmentation. 3D image segmentation, coding scheme, perception

authors: Anahita Sanandaji and Jeremy Deutsch and Max Parola and Meghan Kajihara and Anne Carlew and Ruth West and Cindy Grimm

Authors: Anahita Sanandaji and Jeremy Deutsch and Max Parola and Meghan Kajihara and Anne Carlew and Ruth West and Cindy Grimm