Space-time tomography for continuously deforming objects

Guangming Zang, Ramzi Idoughi, Ran Tao, Gilles Lubineau, Peter Wonka, Wolfgang Heidrich

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

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 languageEnglish (US)
Article numberA61
JournalACM transactions on graphics
Volume37
Issue number4
DOIs
StatePublished - 2018

Keywords

  • 4D reconstruction
  • Optimization
  • X-ray computed tomography

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design

Fingerprint

Dive into the research topics of 'Space-time tomography for continuously deforming objects'. Together they form a unique fingerprint.

Cite this