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

• Published in: Measurement science & technology Vol. 29; no. 1; pp. 14003 - 14018
• Main Authors: Dahl, Vedrana Andersen, Dahl, Anders Bjorholm, Hansen, Per Christian
• Format: Journal Article
• Language: English
• Published: IOP Publishing 01.01.2018
• Subjects: deformable models; parametric curve; segmentation; tomographic reconstruction; x-ray tomography
• ISSN: 0957-0233; 1361-6501; 1361-6501
• DOI: 10.1088/1361-6501/aa950e

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.