New iterative cone beam CT reconstruction software: Parameter optimisation and convergence study

Abstract Cone beam computed tomography (CBCT) provides a volumetric image reconstruction from tomographic projection data. Image quality is the main concern for reconstruction in comparison to conventional CT. The reconstruction algorithm used is clearly important and should be carefully designed, d...

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Bibliographic Details
Published in:Computer methods and programs in biomedicine 2010-11, Vol.100 (2), p.166-174
Main Authors: Qiu, W, Tong, J.R, Mitchell, C.N, Marchant, T, Spencer, P, Moore, C.J, Soleimani, M
Format: Article
Language:English
Subjects:
Algorithms
Biological and medical sciences
CBCT
Down-sampled data
Edge recovery
Internal Medicine
Iterative algorithm
Medical sciences
Other
Radiotherapy. Instrumental treatment. Physiotherapy. Reeducation. Rehabilitation, orthophony, crenotherapy. Diet therapy and various other treatments (general aspects)
Software
Technology. Biomaterials. Equipments. Material. Instrumentation
Tomography, X-Ray Computed - methods
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Summary:Abstract Cone beam computed tomography (CBCT) provides a volumetric image reconstruction from tomographic projection data. Image quality is the main concern for reconstruction in comparison to conventional CT. The reconstruction algorithm used is clearly important and should be carefully designed, developed and investigated before it can be applied clinically. The Multi-Instrument Data Analysis System (MIDAS) tomography software originally designed for geophysical applications has been modified to CBCT image reconstruction. In CBCT reconstruction algorithms, iterative methods offer the potential to generate high quality images and would be an advantage especially for down-sampling projection data. In this paper, studies of the CBCT iterative algorithms implemented in MIDAS are presented. Stability, convergence rate, quality of reconstructed image and edge recovery are suggested as the main criteria for monitoring reconstructive performance. Accordingly, the selection of relaxation parameter and number of iterations are studied in detail. Results are presented, where images are reconstructed from full and down-sampled cone beam CT projection data using iterative algorithms. Various iterative algorithms have been implemented and the best selection of the iteration number and relaxation parameters are investigated for ART. Optimal parameters are chosen where the errors in projected data as well as image errors are minimal.
ISSN:0169-2607
1872-7565
DOI:10.1016/j.cmpb.2010.03.012