Techniques in helical scanning, dynamic imaging and image segmentation for improved quantitative analysis with X-ray micro-CT

NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION B-BEAM INTERACTIONS WITH MATERIALS AND ATOMS

卷:324

Article; Proceedings Paper

Sheppard, Adrian¹  Latham, Shane¹  Middleton, Jill¹  Kingston, Andrew¹  Myers, Glenn¹  Varslot, Trond¹  Fogden, Andrew¹  Sawkins, Tim¹  Cruikshank, Ron¹  Saadatfar, Mohammad¹  Francois, Nicolas¹  Arns, Christoph²  Senden, Tim¹ 

[1] Australian Natl Univ, Dept Appl Math, Res Sch Phys & Engn, Canberra, ACT 0200, Australia

[2] Univ New S Wales, Sch Petr Engn, Sydney, NSW 2052, Australia

关键词: Dynamic tomography;    Helical cone-beam tomography;    Micro-computed tomography;    Image registration;    Image segmentation;   

DOI  :  10.1016/j.nimb.2013.08.072

来源: Elsevier

【 摘 要 】

This paper reports on recent advances at the micro-computed tomography facility at the Australian National University. Since 2000 this facility has been a significant centre for developments in imaging hardware and associated software for image reconstruction, image analysis and image-based modelling. In 2010 a new instrument was constructed that utilises theoretically-exact image reconstruction based on helical scanning trajectories, allowing higher cone angles and thus better utilisation of the available X-ray flux. We discuss the technical hurdles that needed to be overcome to allow imaging with cone angles in excess of 60 degrees. We also present dynamic tomography algorithms that enable the changes between one moment and the next to be reconstructed from a sparse set of projections, allowing higher speed imaging of time-varying samples. Researchers at the facility have also created a sizeable distributed-memory image analysis toolkit with capabilities ranging from tomographic image reconstruction to 3D shape characterisation. We show results from image registration and present some of the new imaging and experimental techniques that it enables. Finally, we discuss the crucial question of image segmentation and evaluate some recently proposed techniques for automated segmentation. (C) 2014 Elsevier B.V. All rights reserved.

【 授权许可】

Free