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Alexander Kostenko

Researcher at Centrum Wiskunde & Informatica

Publications -  17
Citations -  143

Alexander Kostenko is an academic researcher from Centrum Wiskunde & Informatica. The author has contributed to research in topics: Iterative reconstruction & Tomography. The author has an hindex of 5, co-authored 14 publications receiving 99 citations. Previous affiliations of Alexander Kostenko include Delft University of Technology.

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Total variation minimization approach in in-line x-ray phase-contrast tomography

TL;DR: This work investigates how this system can be solved using three different algebraic reconstruction algorithms based on Total Variation minimization and demonstrates that algebraic algorithms may become an important tool in applications where the acquisition time and the delivered radiation dose must be minimized.
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Phase retrieval in in-line x-ray phase contrast imaging based on total variation minimization

TL;DR: The presented method was shown to deliver improved accuracy in reconstructions based on a single distance as well as multiple distance phase-contrast images corrupted by noise and hampered by errors due to nonlinear imaging effects.
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Integrating expert feedback on the spot in a time-efficient explorative CT scanning workflow for cultural heritage objects

TL;DR: This paper shows how a time-efficient explorative workflow can be created for CT investigation of art objects, where the object can be inspected in 3D while still in the scanner, and based on the observations and the resulting new questions, the scanning procedure can be iteratively refined.
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Dating and provenancing the Woman with lantern sculpture – A contribution towards attribution of Netherlandish art

TL;DR: In this paper, the Woman with lantern was found to date to 1487 C.E. and the outermost ring was estimated to have been cut after 1495 C. E., indicating a likely production in the first quarter of the 16th century.
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Prototyping X-ray tomographic reconstruction pipelines with FleXbox

TL;DR: The modular architecture of FleXbox allows to design an optimal reconstruction approach for a single CT dataset, which allows to create a computational reconstruction pipeline that can run without user interaction and enables efficient computation on large-scale 3D volumes on a single workstation.