A Novel Approach for Immediate, Interactive CT Data Visualization and Evaluation using GPU-based Segmentation and Visual Analysis
semanticscholar(2019)
摘要
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.
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