Abstract
X-ray computed tomography (CT) is a valuable tool for analyzing objects with interesting internal structure or complex geometries that are not accessible with optical means. Unfortunately, tomographic reconstruction of complex shapes requires a multitude (often hundreds or thousands) of projections from different viewpoints. Such a large number of projections can only be acquired in a time-sequential fashion. This significantly limits the ability to use x-ray tomography for either objects that undergo uncontrolled shape change at the time scale of a scan, or else for analyzing dynamic phenomena, where the motion itself is under investigation. In thiswork,we present a non-parametric space-time tomographic method for tackling such dynamic settings. Through a combination of a new CT image acquisition strategy, a space-time tomographic image formation model, and an alternating, multi-scale solver, we achieve a general approach that can be used to analyze a wide range of dynamic phenomena.We demonstrate our method with extensive experiments on both real and simulated data.
Original language | English (US) |
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Article number | A61 |
Journal | ACM transactions on graphics |
Volume | 37 |
Issue number | 4 |
DOIs | |
State | Published - 2018 |
Keywords
- 4D reconstruction
- Optimization
- X-ray computed tomography
ASJC Scopus subject areas
- Computer Graphics and Computer-Aided Design
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Data for "Space-time Tomography for Continuously Deforming Objects"
Zang, G. (Creator), Idoughi, R. (Creator), Tao, R. (Creator), Lubineau, G. (Creator), Wonka, P. (Creator), Heidrich, W. (Creator) & Idoughi, R. (Creator), KAUST Research Repository, Apr 26 2018
http://hdl.handle.net/10754/627676
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