Details

Type

  • Master Thesis

Persons

1

Description

Develop an interactive visualization framework that enables scalable comparison of 3D/4D datasets (e.g., medical imaging volumes, 3D simulations, point clouds, or scientific datasets---all potentially over time), allowing users to efficiently explore similarities, differences, and trends across single or multiple volumes without overwhelming the interface.

Key Challenges

  • Visualizing multiple volumetric datasets simultaneously without occlusion.
  • Supporting different comparison modes:
    • 1-to-1: Comparison of two instances.
    • 1-to-Many: Comparing a reference volume against multiple volumes.
    • Many-to-Many: Comparisons across a large collection of volumes.
  • Maintaining interactivity and perceptual clarity while scaling.
  • Efficient data management (GPU/CPU) for large volumetric datasets.
     

Tasks

  • Review the state of the art in comparative visualization
  • Design comparative layouts for 3D/4D data
  • Potentially, develop interaction techniques
  • Implement scalable data handling
  • Evaluation (with a possible benchmark against existing 3D comparison approaches).

Requirements

  • Visualization & computer graphics
  • Experience with volumetric data formats (CT/MRI scans, CFD simulations, etc.)
  • Familiarity with GPU acceleration or large data handling
  • Creativity :) 

References

https://www.sciencedirect.com/science/article/pii/S0097849317300481 

Responsible

For more information please contact Renata Raidou.