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We propose BoneStory, a web-based visual storytelling tool for 3D virtual surgical planning (VSP) to enhance the visual representation in surgical planning. BoneStory allows experts to create and manage multiple plans through an interaction provenance tree consisting of essential user interactions for virtual fracture reduction planning. Furthermore, we simplify this interaction provenance tree by hierarchical grouping and action type filtering to track key interactions faster. We evaluated the usability of our features in a user study where we asked medical experts in trauma surgery to perform surgical planning and create visual stories with BoneStory. Our results indicate that BoneStory effectively aids the experts in authoring visual stories and interaction provenance tracking. Hierarchical grouping was found to increase the efficiency of tracking key actions, being about 45% faster than methods without grouping.

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BoneStory: Visual Storytelling in 3D Virtual Surgical Planning for Bone Fracture Reduction

  • 会议论文

  • 发表日期：

    2025年

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  • Heejun Lee,
  • Peter A. J. Pijpker,
  • Joep Kraeima,
  • Lorenzo Amabili,
  • Fokie Cnossen,
  • Jos B. T. M. Roerdink,
  • Peter M. A. van Ooijen,
  • Jiří Kosinka

摘要

We propose BoneStory, a web-based visual storytelling tool for 3D virtual surgical planning (VSP) to enhance the visual representation in surgical planning. BoneStory allows experts to create and manage multiple plans through an interaction provenance tree consisting of essential user interactions for virtual fracture reduction planning. Furthermore, we simplify this interaction provenance tree by hierarchical grouping and action type filtering to track key interactions faster. We evaluated the usability of our features in a user study where we asked medical experts in trauma surgery to perform surgical planning and create visual stories with BoneStory. Our results indicate that BoneStory effectively aids the experts in authoring visual stories and interaction provenance tracking. Hierarchical grouping was found to increase the efficiency of tracking key actions, being about 45% faster than methods without grouping.