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Title: Geometry and Gesture-Based Features from Saccadic Eye-Movement as a Biometric in Radiology

Abstract

In this study, we present a novel application of sketch gesture recognition on eye-movement for biometric identification and estimating task expertise. The study was performed for the task of mammographic screening with simultaneous viewing of four coordinated breast views as typically done in clinical practice. Eye-tracking data and diagnostic decisions collected for 100 mammographic cases (25 normal, 25 benign, 50 malignant) and 10 readers (three board certified radiologists and seven radiology residents), formed the corpus for this study. Sketch gesture recognition techniques were employed to extract geometric and gesture-based features from saccadic eye-movements. Our results show that saccadic eye-movement, characterized using sketch-based features, result in more accurate models for predicting individual identity and level of expertise than more traditional eye-tracking features.

Authors:
 [1]; ORCiD logo [2]; ORCiD logo [2]; ORCiD logo [2]
  1. Texas A&M University, College Station
  2. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1394217
DOE Contract Number:
AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: International conference for human computer interaction - Vancouver, , Canada - 7/9/2017 12:00:00 AM-
Country of Publication:
United States
Language:
English

Citation Formats

Hammond, Tracy, Tourassi, Georgia, Yoon, Hong-Jun, and Alamudun, Folami T. Geometry and Gesture-Based Features from Saccadic Eye-Movement as a Biometric in Radiology. United States: N. p., 2017. Web.
Hammond, Tracy, Tourassi, Georgia, Yoon, Hong-Jun, & Alamudun, Folami T. Geometry and Gesture-Based Features from Saccadic Eye-Movement as a Biometric in Radiology. United States.
Hammond, Tracy, Tourassi, Georgia, Yoon, Hong-Jun, and Alamudun, Folami T. 2017. "Geometry and Gesture-Based Features from Saccadic Eye-Movement as a Biometric in Radiology". United States. doi:. https://www.osti.gov/servlets/purl/1394217.
@article{osti_1394217,
title = {Geometry and Gesture-Based Features from Saccadic Eye-Movement as a Biometric in Radiology},
author = {Hammond, Tracy and Tourassi, Georgia and Yoon, Hong-Jun and Alamudun, Folami T.},
abstractNote = {In this study, we present a novel application of sketch gesture recognition on eye-movement for biometric identification and estimating task expertise. The study was performed for the task of mammographic screening with simultaneous viewing of four coordinated breast views as typically done in clinical practice. Eye-tracking data and diagnostic decisions collected for 100 mammographic cases (25 normal, 25 benign, 50 malignant) and 10 readers (three board certified radiologists and seven radiology residents), formed the corpus for this study. Sketch gesture recognition techniques were employed to extract geometric and gesture-based features from saccadic eye-movements. Our results show that saccadic eye-movement, characterized using sketch-based features, result in more accurate models for predicting individual identity and level of expertise than more traditional eye-tracking features.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = 2017,
month = 7
}

Conference:
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