Journal article
Computing segmentations directly from x-ray projection data via parametric deformable curves: Paper
Department of Applied Mathematics and Computer Science, Technical University of Denmark1
Statistics and Data Analysis, Department of Applied Mathematics and Computer Science, Technical University of Denmark2
Visual Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark3
Scientific Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark4
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.
Language: | English |
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Year: | 2018 |
Pages: | 014003 |
ISSN: | 13616501 and 09570233 |
Types: | Journal article |
DOI: | 10.1088/1361-6501/aa950e |
ORCIDs: | Dahl, Vedrana Andersen , Dahl, Anders Bjorholm and Hansen, Per Christian |