Direct Visualization of Photographic Volumes

Direct Visualization of Photographic Volumes

Vissers, B.H.

Botha, C.P. (mentor)

Electrical Engineering, Mathematics and Computer Science

Computer Graphics

Mediamatics

2011-10-07

Volume visualization of photographic data is a relatively new domain for medical visualisation. In photographic volumes, voxel colour is predetermined, making colour selection through transfer functions less important, or even unnecessary. However, voxel classi?cation from photographic data is more complex than classi?cation from scalar datasets. Materials and structures in the human body overlap in the colour-space, and are therefore not separable solely by their colour values. In addition, low contrast between some of the adjacent materials and structures in the data complicates the use of boundary-based classi?cation techniques. In the ?rst half of this work we investigate the differences between volume visualization of scalar datasets and volume visualization of photographic datasets. We study a broad range of techniques which could be extended for photographic data, or replace traditional techniques in the volume render pipeline. In addition we study normal estimation for photographic data, which suffers from the non-linear colour spaces and previously mentioned low contrast. In the second half of this work we present an example-based visualization system which does not require its user to understand the mechanics of volume visualization. Our target group are non-visualization experts who want to use volume visualization to provide insight into their data. The system uses live rendered style previews which can be combined to form a composite render style. The system supports multiple photorealistic as well as illustrative render techniques and can apply any combination of these techniques to any object in the dataset, rendering comprehensible images. The effectiveness of our system is demonstrated by experimental results on real volumetric data.

visualization
raycasting
medical
photographic data

http://resolver.tudelft.nl/uuid:9192b18f-e3ca-4595-ace5-edbcc12f1e06

2011-10-15

Student theses

master thesis

(c) 2011 Vissers, B.H.