Computing segmentations directly from x-ray projection data via parametric deformable curves: Paper

Research output: Contribution to journalJournal article – Annual report year: 2018Researchpeer-review



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We describe an efficient algorithm that computes a segmented reconstruction directly from x-ray projection data. Our algorithm uses a parametric curve to define the segmentation. Unlike similar approaches which are based on level-sets, our method avoids a pixel or voxel grid; hence the number of unknowns is reduced to the set of points that define the curve, and attenuation coefficients of the segments. Our current implementation uses a simple closed curve and is capable of separating one object from the background. However, our basic algorithm can be applied to an arbitrary topology and multiple objects corresponding to different attenuation coefficients in the reconstruction. Through systematic tests we demonstrate a high robustness to the noise, and an excellent performance under a small number of projections.
Original languageEnglish
Article number014003
JournalMeasurement Science and Technology
Issue number1
Number of pages16
Publication statusPublished - 2018
CitationsWeb of Science® Times Cited: No match on DOI

    Research areas

  • X-ray tomography, Segmentation, Tomographic reconstruction, Deformable models, Parametric curve
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