Abstract #1346

Eye Tracking System for Prostate Cancer Diagnosis Using Multi-Parametric MRI

Haydar Celik^1,2,3, Baris Ismail Turkbey⁴, Peter Choyke⁴, Ruida Cheng⁵, Evan McCreedy⁵, Matthew McAuliffe⁵, Naji Khosravan⁶, Ulas Bagci⁶, and Bradford J Wood¹

¹Clinical Center, National Institutes of Health, Bethesda, MD, United States, ²SZI, Children's National Health System, Washington, DC, United States, ³Pediatrics, George Washington University, Washington, DC, United States, ⁴NCI, National Institutes of Health, Bethesda, MD, United States, ⁵CIT, National Institutes of Health, Bethesda, MD, United States, ⁶Center for Research in Computer Vision, University of Central Florida, Orlando, FL, United States

Medical images have been studied using eye tracker systems from visual search and perception perspectives since 1960’s. However number of studies for the multi slice imaging is very limited due to the technical challenges. We developed a software to overcome the difficulties, and enable visual search/perception studies using multi-parametric MRI of prostate cancer. Multiparametric MR images (T2w, DWI, ADC map, and DCE) were synchronized with the eye tracker system and visual-attention maps were successfully created for each image types using gaze information. This is the first multiparametric MR study using an eye tracker system.

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