Compressed Sensing based Micro-CT Methods and Applications
| dc.contributor.author | Sen Sharma, Kriti | en |
| dc.contributor.committeechair | Wang, Ge | en |
| dc.contributor.committeemember | Wyatt, Chris L. | en |
| dc.contributor.committeemember | Polys, Nicholas F. | en |
| dc.contributor.committeemember | Xiao, Shuhai | en |
| dc.contributor.committeemember | da Silva, Claudio R. C. M. | en |
| dc.contributor.department | Electrical and Computer Engineering | en |
| dc.date.accessioned | 2015-05-30T06:01:21Z | en |
| dc.date.available | 2015-05-30T06:01:21Z | en |
| dc.date.issued | 2013-06-12 | en |
| dc.description.abstract | High-resolution micro computed tomography (micro-CT) offers 3D image resolution of 1 um for non-destructive evaluation of various samples. However, the micro-CT performance is limited by several factors. Primarily, scan time is extremely long, and sample dimension is restricted by the x-ray beam and the detector size. The latter is the cause for the well-known interior problem. Recent advancement in image reconstruction, spurred by the advent of compressed sensing (CS) theory in 2006 and interior tomography theory since 2007, offers great reduction in the number of views and an increment in the volume of samples, while maintaining reconstruction accuracy. Yet, for a number of reasons, traditional filtered back-projection based reconstruction methods remain the de facto standard on all manufactured scanners. This work demonstrates that CS based global and interior reconstruction methods can enhance the imaging capability of micro-CT scanners. First, CS based few-view reconstruction methods have been developed for use with data from a real micro-CT scanner. By achieving high quality few-view reconstruction, the new approach is able to reduce micro-CT scan time to up to 1/8th of the time required by the conventional protocol. Next, two new reconstruction techniques have been developed that allow accurate interior reconstruction using just a limited number of global scout views as additional information. The techniques represent a significant progress relative to the previous methods that assume a fully sampled global scan. Of the two methods, the second method uses CS techniques and does not place any restrictions on scanning geometry. Finally, analytic and iterative reconstruction methods have been developed for enlargement of the field of view for the interior scan with a small detector. The idea is that truncated projections are acquired in an offset detector geometry, and the reconstruction procedure is performed through the use of a weighting function / weighted iteration updates, and projection completion. The CS based reconstruction yields the highest image quality in the numerical simulation. Yet, some limitations of the CS based techniques are observed in case of real data with various imperfect properties. In all the studies, physical micro-CT phantoms have been designed and utilized for performance analysis. Also, important guidelines are suggested for future improvements. | en |
| dc.description.degree | Ph. D. | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:951 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/52866 | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | x-ray computed tomography | en |
| dc.subject | micro-ct | en |
| dc.subject | image reconstruction | en |
| dc.subject | compressed sensing | en |
| dc.subject | iterative reconstruction | en |
| dc.subject | few-view | en |
| dc.subject | interior tomography | en |
| dc.title | Compressed Sensing based Micro-CT Methods and Applications | en |
| dc.type | Dissertation | en |
| thesis.degree.discipline | Electrical Engineering | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | doctoral | en |
| thesis.degree.name | Ph. D. | en |
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