Where Do Neurologists Look When Viewing Brain CT Images? An Eye-Tracking Study Involving Stroke Cases

The aim of this study was to investigate where neurologists look when they view brain computed tomography (CT) images and to evaluate how they deploy their visual attention by comparing their gaze distribution with saliency maps. Brain CT images showing cerebrovascular accidents were presented to 12 neurologists and 12 control subjects. The subjects' ocular fixation positions were recorded using an eye-tracking device (Eyelink 1000). Heat maps were created based on the eye-fixation patterns of each group and compared between the two groups. The heat maps revealed that the areas on which control subjects frequently fixated often coincided with areas identified as outstanding in saliency maps, while the areas on which neurologists frequently fixated often did not. Dwell time in regions of interest (ROI) was likewise compared between the two groups, revealing that, although dwell time on large lesions was not different between the two groups, dwell time in clinically important areas with low salience was longer in neurologists than in controls. Therefore it appears that neurologists intentionally scan clinically important areas when reading brain CT images showing cerebrovascular accidents. Both neurologists and control subjects used the “bottom-up salience” form of visual attention, although the neurologists more effectively used the “top-down instruction” form.

[1]  R. Hanajima,et al.  Small saccades restrict visual scanning area in Parkinson's disease , 2011, Movement disorders : official journal of the Movement Disorder Society.

[2]  J. Barton,et al.  Fixation and saliency during search of natural scenes: The case of visual agnosia , 2009, Neuropsychologia.

[3]  M. Land Vision, eye movements, and natural behavior , 2009, Visual Neuroscience.

[4]  Claudia Mello-Thoms,et al.  Using gaze-tracking data and mixture distribution analysis to support a holistic model for the detection of cancers on mammograms. , 2008, Academic radiology.

[5]  J. Khoury,et al.  Eye Position Information on CT Increases the Identification of Acute Ischemic Hypoattenuation , 2008, American Journal of Neuroradiology.

[6]  T. Foulsham,et al.  What can saliency models predict about eye movements? Spatial and sequential aspects of fixations during encoding and recognition. , 2008, Journal of vision.

[7]  E. Conant,et al.  Holistic component of image perception in mammogram interpretation: gaze-tracking study. , 2007, Radiology.

[8]  Pietro Perona,et al.  Graph-Based Visual Saliency , 2006, NIPS.

[9]  D. Hansell,et al.  Thin-section CT of the lungs: eye-tracking analysis of the visual approach to reading tiled and stacked display formats. , 2006, European journal of radiology.

[10]  Gary L. Allen,et al.  Seeking a Common Gestalt Approach to the Perception of Faces, Objects, and Scenes , 2006 .

[11]  Wieske van Zoest,et al.  Bottom-up and Top-down Control in Visual Search , 2004, Perception.

[12]  Claudia Mello-Thoms,et al.  Time course of perception and decision making during mammographic interpretation. , 2002, AJR. American journal of roentgenology.

[13]  Casimir J. H. Ludwig,et al.  Stimulus-driven and goal-driven control over visual selection. , 2002, Journal of experimental psychology. Human perception and performance.

[14]  T. Yosue,et al.  Analyzing the eye movement of dentists during their reading of CT images , 2001, Odontology.

[15]  C. Koch,et al.  Computational modelling of visual attention , 2001, Nature Reviews Neuroscience.

[16]  C. Koch,et al.  A saliency-based search mechanism for overt and covert shifts of visual attention , 2000, Vision Research.

[17]  C. Koch,et al.  A Model of Saliency-Based Visual Attention for Rapid Scene Analysis , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  David V. Beard,et al.  Eye movement during computed tomography interpretation: Eyetracker results and image display-time implications , 1994, Journal of Digital Imaging.

[19]  H L Kundel,et al.  Searching for bone fractures: a comparison with pulmonary nodule search. , 1994, Academic radiology.

[20]  David V. Beard,et al.  A study of radiologists viewing multiple computed tomography examinations using an eyetracking device , 1990, Journal of Digital Imaging.

[21]  D. Navon Forest before trees: The precedence of global features in visual perception , 1977, Cognitive Psychology.

[22]  Michael L. Mack,et al.  VISUAL SALIENCY DOES NOT ACCOUNT FOR EYE MOVEMENTS DURING VISUAL SEARCH IN REAL-WORLD SCENES , 2007 .

[23]  S. Ullman,et al.  Shifts in selective visual attention: towards the underlying neural circuitry. , 1985, Human neurobiology.

[24]  Ming-Hsuan Yang,et al.  Learning to recognize objects , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).