Algorithms for MARS spectral CT.
Thesis DisciplineMedical Physics
Degree GrantorUniversity of Canterbury
Degree NameMaster of Science
This thesis reports on algorithmic design and software development completed for the Medipix All Resolution System (MARS) multi-energy CT scanner. Two areas of research are presented - the speed and usability improvements made to the post-reconstruction material decomposition software; and the development of two algorithms designed for the implementation of a novel voxel system into the MARS image reconstruction chain. The MARS MD software package is the primary material analysis tool used by members of the MARS group. The photon-processing ability of the MARS scanner is what makes material decomposition possible. MARS MD loads reconstructed images created after a scan and creates a new set of images, one for every individual material within the object. The software is capable of discriminating at least six different materials, plus air, within the object. A significant speed improvement to this program was attained by moving the code base from GNU Octave to MATLAB and applying well known optimisation routines, while the creation of a graphical user interface made the software more accessible and easy to use. The changes made to MARS MD represented a significant contribution to the productivity of the entire MARS group. A drawback of the MARS image reconstruction chain is the time required to generate images of a scanned object. Compared to commercially available CT systems, the MARS system takes several orders of magnitude longer to do essentially the same job. With up to eight energy bins worth of data to consider during reconstruction, compared to a single energy bin in most com- mercial scanners, it is not surprising that there is a shortfall. A major performance limitation of the reconstruction process lies in the calculation of the small distances travelled by every detected photon within individual portions of the reconstruction volume. This thesis investigates a novel volume geometry that was developed by Prof. Phil Butler and Dr. Peter Renaud, and is designed to partially mitigate this time constraint. By treating the volume as a cylinder instead of a traditional cubic structure, the number of individual path length calculations can be drastically reduced. Two sets of algorithms are prototyped, coded in MATLAB, C++ and CUDA, and finally compared in terms of speed and visual accuracy.