Scanpath comparison in medical image reading skills of dental students

Nora Castner, Enkelejda Kasneci, Thomas Kübler, Katharina Scheiter, Juliane Richter, Thérése Eder, Fabian Hüttig, Constanze Keutel

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

32 Scopus citations


A popular topic in eye tracking is the difference between novices and experts and their domain-specific eye movement behaviors. However, very little is researched regarding how expertise develops, and more specifically, the developmental stages of eye movement behaviors. Our work compares the scanpaths of five semesters of dental students viewing orthopantomograms (OPTs) with classifiers to distinguish sixth semester through tenth semester students. We used the analysis algorithm SubsMatch 2.0 and the Needleman-Wunsch algorithm. Overall, both classifiers were able distinguish the stages of expertise in medical image reading above chance level. Specifically, it was able to accurately determine sixth semester students with no prior training as well as sixth semester students after training. Ultimately, using scanpath models to recognize gaze patterns characteristic of learning stages, we can provide more adaptive, gaze-based training for students.

Original languageEnglish
Title of host publicationProceedings - ETRA 2018
Subtitle of host publication2018 ACM Symposium on Eye Tracking Research and Applications
EditorsStephen N. Spencer
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450357067
StatePublished - 14 Jun 2018
Externally publishedYes
Event10th ACM Symposium on Eye Tracking Research and Applications, ETRA 2018 - Warsaw, Poland
Duration: 14 Jun 201817 Jun 2018

Publication series

NameEye Tracking Research and Applications Symposium (ETRA)


Conference10th ACM Symposium on Eye Tracking Research and Applications, ETRA 2018


  • Learning
  • Medical image interpretation
  • Remote Eye Tracking
  • Scanpath analysis


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