11th EAI International Conference on Pervasive Computing Technologies for Healthcare

Research Article

Applying trajectory mining in medical image data

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1145/3154862.3154889,
    author={Roland Ellerweg and Katharina Hofer and Artur Khromov and Peter Voigt and Sebastian Fischer},
    title={Applying trajectory mining in medical image data},
    proceedings={11th EAI International Conference on Pervasive Computing Technologies for Healthcare},
    publisher={ACM},
    proceedings_a={PERVASIVEHEALTH},
    year={2018},
    month={1},
    keywords={radiology; data mining; trajectory; medical imaging; user experiment},
    doi={10.1145/3154862.3154889}
}
  • Roland Ellerweg
    Katharina Hofer
    Artur Khromov
    Peter Voigt
    Sebastian Fischer
    Year: 2018
    Applying trajectory mining in medical image data
    PERVASIVEHEALTH
    ACM
    DOI: 10.1145/3154862.3154889
Roland Ellerweg1,*, Katharina Hofer1, Artur Khromov1, Peter Voigt2, Sebastian Fischer3
  • 1: Fraunhofer FIT
  • 2: University Hospital Leipzig
  • 3: University Hospotal Frankfurt
*Contact email: r.ellerweg@gmx.de

Abstract

During evaluation of CT or MR images radiologists navigate through a volume in different orientations in order to detect a disease. While doing so, they leave a trail, which might hold valuable information for other clinicians. Unfortunately, current systems do not analyze this trail for certain motions or potential patterns. In this work we developed and implemented different strategies to infer the manifestation of a disease from the trail of inspection. Furthermore we evaluate the effectiveness of these strategies by conducting an experiment in which clinicians had to find a tumor in several cases. The results suggest that inferring suspicious areas from the trail is possible.

Keywords
radiology; data mining; trajectory; medical imaging; user experiment
Published
2018-01-16
Publisher
ACM
http://dx.doi.org/10.1145/3154862.3154889
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