Effectiveness of Visualisations for Detection of Errors in Segmentation of Blood Vessels

B.W. van Schooten, Elisabeth M.A.G. van Dijk, A. Suinesiaputra, J.H.C. Reiber

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

    2 Citations (Scopus)
    35 Downloads (Pure)

    Abstract

    Vascular disease diagnosis often requires a precise segmentation of the vessel lumen. When 3D (Magnetic Resonance Angiography, MRA, or Computed Tomography Angiography, CTA) imaging is available, this can be done automatically, but occasional errors are inevitable. So, the segmentation has to be checked by clinicians. This requires appropriate visualisation techniques. A number of visualisation techniques exist, but there has been little in the way of user studies that compare the different alternatives. In this study we examine how users interact with several basic visualisations, when performing a visual search task, checking vascular segmentation correctness of segmented MRA data. These visualisations are: direct volume rendering (DVR), isosurface rendering, and curved planar reformatting (CPR). Additionally, we examine if visual highlighting of potential errors can help the user find errors, so a fourth visualisation we examine is DVR with visual highlighting. Our main findings are that CPR performs fastest but has higher error rate, and there are no significant differences between the other three visualisations. We did find that visual highlighting actually has slower performance in early trials, suggesting that users learned to ignore them.
    Original languageUndefined
    Title of host publicationInternational Conference on Information Visualization Theory and Applications, IVAPP 2010
    Place of PublicationAngers, France
    PublisherINSTICC PRESS
    Pages77-84
    Number of pages8
    ISBN (Print)978-989-674-028-3
    Publication statusPublished - 17 May 2010

    Publication series

    Name
    PublisherINSTICC Press

    Keywords

    • METIS-270894
    • MRA
    • IR-72273
    • EWI-18099
    • Visual cues
    • Radiology
    • Segmentation
    • Volume visualization

    Cite this

    van Schooten, B. W., van Dijk, E. M. A. G., Suinesiaputra, A., & Reiber, J. H. C. (2010). Effectiveness of Visualisations for Detection of Errors in Segmentation of Blood Vessels. In International Conference on Information Visualization Theory and Applications, IVAPP 2010 (pp. 77-84). Angers, France: INSTICC PRESS.
    van Schooten, B.W. ; van Dijk, Elisabeth M.A.G. ; Suinesiaputra, A. ; Reiber, J.H.C. / Effectiveness of Visualisations for Detection of Errors in Segmentation of Blood Vessels. International Conference on Information Visualization Theory and Applications, IVAPP 2010. Angers, France : INSTICC PRESS, 2010. pp. 77-84
    @inproceedings{a3a6f0ee63644c0e928f72838220d1db,
    title = "Effectiveness of Visualisations for Detection of Errors in Segmentation of Blood Vessels",
    abstract = "Vascular disease diagnosis often requires a precise segmentation of the vessel lumen. When 3D (Magnetic Resonance Angiography, MRA, or Computed Tomography Angiography, CTA) imaging is available, this can be done automatically, but occasional errors are inevitable. So, the segmentation has to be checked by clinicians. This requires appropriate visualisation techniques. A number of visualisation techniques exist, but there has been little in the way of user studies that compare the different alternatives. In this study we examine how users interact with several basic visualisations, when performing a visual search task, checking vascular segmentation correctness of segmented MRA data. These visualisations are: direct volume rendering (DVR), isosurface rendering, and curved planar reformatting (CPR). Additionally, we examine if visual highlighting of potential errors can help the user find errors, so a fourth visualisation we examine is DVR with visual highlighting. Our main findings are that CPR performs fastest but has higher error rate, and there are no significant differences between the other three visualisations. We did find that visual highlighting actually has slower performance in early trials, suggesting that users learned to ignore them.",
    keywords = "METIS-270894, MRA, IR-72273, EWI-18099, Visual cues, Radiology, Segmentation, Volume visualization",
    author = "{van Schooten}, B.W. and {van Dijk}, {Elisabeth M.A.G.} and A. Suinesiaputra and J.H.C. Reiber",
    year = "2010",
    month = "5",
    day = "17",
    language = "Undefined",
    isbn = "978-989-674-028-3",
    publisher = "INSTICC PRESS",
    pages = "77--84",
    booktitle = "International Conference on Information Visualization Theory and Applications, IVAPP 2010",

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    van Schooten, BW, van Dijk, EMAG, Suinesiaputra, A & Reiber, JHC 2010, Effectiveness of Visualisations for Detection of Errors in Segmentation of Blood Vessels. in International Conference on Information Visualization Theory and Applications, IVAPP 2010. INSTICC PRESS, Angers, France, pp. 77-84.

    Effectiveness of Visualisations for Detection of Errors in Segmentation of Blood Vessels. / van Schooten, B.W.; van Dijk, Elisabeth M.A.G.; Suinesiaputra, A.; Reiber, J.H.C.

    International Conference on Information Visualization Theory and Applications, IVAPP 2010. Angers, France : INSTICC PRESS, 2010. p. 77-84.

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

    TY - GEN

    T1 - Effectiveness of Visualisations for Detection of Errors in Segmentation of Blood Vessels

    AU - van Schooten, B.W.

    AU - van Dijk, Elisabeth M.A.G.

    AU - Suinesiaputra, A.

    AU - Reiber, J.H.C.

    PY - 2010/5/17

    Y1 - 2010/5/17

    N2 - Vascular disease diagnosis often requires a precise segmentation of the vessel lumen. When 3D (Magnetic Resonance Angiography, MRA, or Computed Tomography Angiography, CTA) imaging is available, this can be done automatically, but occasional errors are inevitable. So, the segmentation has to be checked by clinicians. This requires appropriate visualisation techniques. A number of visualisation techniques exist, but there has been little in the way of user studies that compare the different alternatives. In this study we examine how users interact with several basic visualisations, when performing a visual search task, checking vascular segmentation correctness of segmented MRA data. These visualisations are: direct volume rendering (DVR), isosurface rendering, and curved planar reformatting (CPR). Additionally, we examine if visual highlighting of potential errors can help the user find errors, so a fourth visualisation we examine is DVR with visual highlighting. Our main findings are that CPR performs fastest but has higher error rate, and there are no significant differences between the other three visualisations. We did find that visual highlighting actually has slower performance in early trials, suggesting that users learned to ignore them.

    AB - Vascular disease diagnosis often requires a precise segmentation of the vessel lumen. When 3D (Magnetic Resonance Angiography, MRA, or Computed Tomography Angiography, CTA) imaging is available, this can be done automatically, but occasional errors are inevitable. So, the segmentation has to be checked by clinicians. This requires appropriate visualisation techniques. A number of visualisation techniques exist, but there has been little in the way of user studies that compare the different alternatives. In this study we examine how users interact with several basic visualisations, when performing a visual search task, checking vascular segmentation correctness of segmented MRA data. These visualisations are: direct volume rendering (DVR), isosurface rendering, and curved planar reformatting (CPR). Additionally, we examine if visual highlighting of potential errors can help the user find errors, so a fourth visualisation we examine is DVR with visual highlighting. Our main findings are that CPR performs fastest but has higher error rate, and there are no significant differences between the other three visualisations. We did find that visual highlighting actually has slower performance in early trials, suggesting that users learned to ignore them.

    KW - METIS-270894

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    KW - IR-72273

    KW - EWI-18099

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    KW - Radiology

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    KW - Volume visualization

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    SN - 978-989-674-028-3

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    BT - International Conference on Information Visualization Theory and Applications, IVAPP 2010

    PB - INSTICC PRESS

    CY - Angers, France

    ER -

    van Schooten BW, van Dijk EMAG, Suinesiaputra A, Reiber JHC. Effectiveness of Visualisations for Detection of Errors in Segmentation of Blood Vessels. In International Conference on Information Visualization Theory and Applications, IVAPP 2010. Angers, France: INSTICC PRESS. 2010. p. 77-84