Browsing by Author "Dragicevic, Pierre"

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    Reducing Affective Responses to Surgical Images and Videos Through Stylization
    (© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Besançon, Lonni; Semmo, Amir; Biau, David; Frachet, Bruno; Pineau, Virginie; Sariali, El Hadi; Soubeyrand, Marc; Taouachi, Rabah; Isenberg, Tobias; Dragicevic, Pierre; Benes, Bedrich and Hauser, Helwig
    We present the first empirical study on using colour manipulation and stylization to make surgery images/videos more palatable. While aversion to such material is natural, it limits many people's ability to satisfy their curiosity, educate themselves and make informed decisions. We selected a diverse set of image processing techniques to test them both on surgeons and lay people. While colour manipulation techniques and many artistic methods were found unusable by surgeons, edge‐preserving image smoothing yielded good results both for preserving information (as judged by surgeons) and reducing repulsiveness (as judged by lay people). We then conducted a second set of interview with surgeons to assess whether these methods could also be used on videos and derive good default parameters for information preservation. We provide extensive supplemental material at .
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    Reducing Affective Responses to Surgical Images through Color Manipulation and Stylization
    (ACM, 2018) Besançon, Lonni; Semmo, Amir; Biau, David; Frachet, Bruno; Pineau, Virginie; Sariali, El Hadi; Taouachi, Rabah; Isenberg, Tobias; Dragicevic, Pierre; Aydın, Tunç and Sýkora, Daniel
    We present the first empirical study on using color manipulation and stylization to make surgery images more palatable. While aversion to such images is natural, it limits many people's ability to satisfy their curiosity, educate themselves, and make informed decisions. We selected a diverse set of image processing techniques, and tested them both on surgeons and lay people. While many artistic methods were found unusable by surgeons, edge-preserving image smoothing gave good results both in terms of preserving information (as judged by surgeons) and reducing repulsiveness (as judged by lay people). Color manipulation turned out to be not as effective.
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    A Survey of Tasks and Visualizations in Multiverse Analysis Reports
    (© 2022 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2022) Hall, Brian D.; Liu, Yang; Jansen, Yvonne; Dragicevic, Pierre; Chevalier, Fanny; Kay, Matthew; Hauser, Helwig and Alliez, Pierre
    Analysing data from experiments is a complex, multi‐step process, often with multiple defensible choices available at each step. While analysts often report a single analysis without documenting how it was chosen, this can cause serious transparency and methodological issues. To make the sensitivity of analysis results to analytical choices transparent, some statisticians and methodologists advocate the use of ‘multiverse analysis’: reporting the full range of outcomes that result from all combinations of defensible analytic choices. Summarizing this combinatorial explosion of statistical results presents unique challenges; several approaches to visualizing the output of multiverse analyses have been proposed across a variety of fields (e.g. psychology, statistics, economics, neuroscience). In this article, we (1) introduce a consistent conceptual framework and terminology for multiverse analyses that can be applied across fields; (2) identify the tasks researchers try to accomplish when visualizing multiverse analyses and (3) classify multiverse visualizations into ‘archetypes’, assessing how well each archetype supports each task. Our work sets a foundation for subsequent research on developing visualization tools and techniques to support multiverse analysis and its reporting.