- Hyunjoo Song, Seoul National University, Seoul, Republic of Korea
- Jihye Yun, Seoul National University, Seoul, Republic of Korea
- Bohyoung Kim, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
- Jinwook Seo, Seoul National University, Seoul, Republic of Korea
Gaze visualization has been used in the medical field to understand how radiologists read medical images. While prior works were mainly based on diagnoses with a single image, recent works focus on diagnoses with consecutive cross-sectional medical images acquired from preoperative computed tomography (CT) or magnetic resonance imaging (MRI). Such images have distinct characteristics that hundreds of them are from a single exam composing a natural 3D spatial structure. Radiologists have to scroll through a stack of the images for a diagnosis, resulting in more complicated gaze patterns to visualize. Little work has been done on visualizing such gaze patterns for contiguous cross-sectional medical images. We present an interactive 3D gaze visualization, where InfoVis and SciVis techniques are harmonized to show the abstract gaze data along with a realistic 3D rendering of the visual stimuli (i.e. organs and lesions).