Interactive Occlusion-Free System for Accessible Volume Exploration

Jing Ru Sun, Nathania Josephine, Chao Wang, Ko Chih Wang*


研究成果: 雜誌貢獻期刊論文同行評審


When exploring a 3D medical dataset, data occlusion creates difficulties for users to understand the dataset in detail since many internal structures are occluded. Techniques such as transfer function design, isosurface extraction, etc., have been proposed in the past to address the occlusion problem and assist expert users in exploring volumetric data. However, these techniques may not be feasible for some non-expert users' scenarios, such as science museum visitors exploring a brain CT image data volume on a large touch screen or high school students learning the human body structure on a tablet because they have no need to conduct long-term data exploration and rigorous scientific analysis. To address the non-expert users' need for an easy-to-use data exploration tool, we propose an interactive data exploration system for non-expert users to interact with the dataset with a short learning time and simple inputs. Non-expert users can remove the obstructing material to reveal the occluded structures by simply clicking on the obstructing material. Our system also preserves the context for non-expert users to understand the dataset after the obstructing material is removed easily. Additionally, for data providers such as the engineers in a museum, our system provides a semi-automatic workflow to set up a dataset into our system for non-expert users. In this work, we conduct two user studies to evaluate our system's usability.

頁(從 - 到)86544-86560
期刊IEEE Access
出版狀態已發佈 - 2023

ASJC Scopus subject areas

  • 一般電腦科學
  • 一般材料科學
  • 一般工程


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