Where do experts look while doing 3D image segmentation

Anahita Sanandaji, Cindy Grimm, Ruth West, Max Parola, Meghan Kajihara, Jeremy Deutsch, Anne Carlew, Deniece Yates

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

3D image segmentation is a fundamental process in many scientific and medical applications. Automatic algorithms do exist, but there are many use cases where these algorithms fail. The gold standard is still manual segmentation or review. Unfortunately, even for an expert this is laborious, time consuming, and prone to errors. Existing 3D segmentation tools do not currently take into account human mental models and low-level perception tasks. Our goal is to improve the quality and efficiency of manual segmentation and review by analyzing how experts perform segmentation. As a pre-Uminary step we conducted a field study with 8 segmentation experts, recording video and eye tracking data. We developed a novel coding scheme to analyze this data and verified that it successfully covers and quantifies the low-level actions, tasks and behaviors of experts during 3D image segmentation.

Original languageEnglish (US)
Title of host publicationProceedings - ETRA 2016
Subtitle of host publication2016 ACM Symposium on Eye Tracking Research and Applications
EditorsStephen N. Spencer
PublisherAssociation for Computing Machinery
Pages171-174
Number of pages4
ISBN (Electronic)9781450341257
DOIs
StatePublished - Mar 14 2016
Externally publishedYes
Event9th Biennial ACM Symposium on Eye Tracking Research and Applications, ETRA 2016 - Charleston, United States
Duration: Mar 14 2016Mar 17 2016

Publication series

NameEye Tracking Research and Applications Symposium (ETRA)
Volume14

Conference

Conference9th Biennial ACM Symposium on Eye Tracking Research and Applications, ETRA 2016
CountryUnited States
CityCharleston
Period3/14/163/17/16

Keywords

  • 3D image segmentation
  • Coding scheme
  • Perception

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Ophthalmology
  • Sensory Systems

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