Papers

1

Total Citations

16

H-Index

1

About

Victor Bussy is a leading figure in computational imaging and non-destructive evaluation, with a core focus on industrial X-ray Computed Tomography (CT). His research centers on developing fast, intelligent algorithms that dramatically reduce the number of radiographies needed for high-quality CT scans, a critical bottleneck in mass production quality control. Bussy’s major contribution lies in pioneering the application of Empirical Interpolation Methods (EIM) to select the most informative projections for sparse-view CT reconstruction. His 2022 paper on this topic, which has garnered 16 citations, demonstrates how a priori information can guide the selection process, enabling accurate 3D inspection of critical parts with significantly fewer projections—a breakthrough for both speed and safety in industrial settings. This work bridges advanced numerical analysis with practical engineering, offering a path to faster, more efficient non-destructive testing. Bussy’s algorithms are poised to reshape dimensional conformity checks, making high-throughput CT inspection viable for demanding applications like aerospace and automotive manufacturing.

Research Focus

Key Achievements

1
H-Index
1
Papers
16
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
Fast algorithms based on Empirical Interpolation Methods for selecting best projections in Sparse-View X-ray Computed Tomography using a priori information
16 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: Commissariat à l'Énergie Atomique et aux Énergies Alternatives

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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