Interactive Occlusion-Free System for Accessible Volume Exploration

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)86544-86560
Number of pages17
JournalIEEE Access
Publication statusPublished - 2023


  • 3D data visualization and exploration
  • human-computer interaction
  • occlusion management

ASJC Scopus subject areas

  • General Computer Science
  • General Materials Science
  • General Engineering


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