@inproceedings{PB-VRVis-2019-003,
author = {Steinlechner, Harald and Haaser, Georg and Oberdorfer, Bernd and Habe, Daniel and Maierhofer, Stefan and Schw{\"a}rzler, Michael and Gr{\"o}ller, Eduard},
title = {A Novel Approach for Immediate, Interactive CT Data
  Visualization and Evaluation using GPU-based Segmentation
  and Visual Analysis},
year = {2019},
booktitle = {International Conference on Industrial Computed Tomography
  (ICT) 2019},
editor = {Simone Carmignato},
url = {https://www.vrvis.at/publications/PB-VRVis-2019-003},
abstract = {CT data of industrially produced cast metal parts are often  afflicted with artefacts due to complex geometries ill-suited  for the scanning process. Simple global threshold-based  porosity detection algorithms usually fail to deliver  meaningful results. Other adaptive methods can handle image  artefacts, but require long preprocessing times. This makes an  efficient analysis workflow infeasible. We propose an  alternative approach for analyzing and visualizing volume  defects in a fully interactive manner, where analyzing volumes  becomes more of an interactive exploration instead of  time-consuming parameter guessing interrupted by long  processing times. Our system is based on a highly efficient GPU  implementation of a segmentation algorithm for porosity  detection. The runtime is on the order of seconds for a full  volume and parametrization is kept simple due to a single  threshold parameter. A fully interactive user interface  comprised of multiple linked views allows to quickly identify  defects of interest, while filtering out artefacts even in  noisy areas.},
keywords = {CT, GPU, Inclusion Detection, Interactive Visualisation, Visual
  Analysis, Parallel Coordinates, Volume Rendering},
}