We present “dynamic tomography” algorithms that allow for the high-resolution, time-resolved imaging of dynamic (i.e., continuously time evolving) complex systems at existing x-ray micro-CT facilities. The behavior of complex systems is constrained by the underlying physics. By exploiting a priori knowledge of the geometry of the physical process being studied to allow the use of sophisticated iterative reconstruction techniques that incorporate constraints, we improve on current frame rates by at least an order of magnitude. This allows time-resolved imaging of previously intractable processes, such as two-phase fluid flow. We present reconstructions from experimental data collected at the Australian National University x-ray micro-CT facility.
© 2011 Optical Society of America
Original Manuscript: January 18, 2011
Revised Manuscript: April 19, 2011
Manuscript Accepted: May 9, 2011
Published: July 8, 2011
Vol. 6, Iss. 8 Virtual Journal for Biomedical Optics
Glenn R. Myers, Andrew M. Kingston, Trond K. Varslot, Michael L. Turner, and Adrian P. Sheppard, "Dynamic tomography with a priori information," Appl. Opt. 50, 3685-3690 (2011)