![](bg1.png)
ITERATIVE IMAGE RECONSTRUCTION METHODS IN CONE
BEAM CT APPLIED TO PHANTOM AND CLINICAL DATA
W. Qiu, M. Soleimani, C. N. Mitchell
Dept. of Electronic and Electrical Engineering, University of Bath, Bath, BA2 7AY, U.K.
T. Marchant, C. J. Moore
The Christie NHS Foundation Trust, Wilmslow Road, Manchester, M20 4BX, U.K.
Keywords:
Iterative reconstruction algorithms, Cone beam CT.
Abstract:
Cone beam computed tomography (CBCT) enables a volumetric image reconstruction from 2D projection
data. In CBCT reconstruction, iterative methods of image reconstruction offer the potential to generate high
quality images and would be an advantage especially for sparse data sets. CBCT image reconstruction software
has been developed based on Multi-Instrument Data Analysis System (MIDAS) tomography toolbox. In this
paper, we present a comparative study of SIRT and ART algorithms, developed in MIDAS platform. The
results will be shown using phantom and clinical patient data.
1 INTRODUCTION
Cone beam computed tomography (CBCT) provides
a volumetric image reconstruction from tomographic
projection data, while in commercial CT system,
though many algorithms exist, filtered back projec-
tion (FBP) like reconstruction algorithm based on
FDK (Feldkamp et al., 1984) is still being used.
Recently, iterative reconstruction algorithms are be-
ing investigated for clinical application (Wang et al.,
2009), as challenges still exist for image reconstruc-
tion due to computational time, parameters selec-
tion and down sampled data in some practical ap-
plications. Iterative algorithms provides an alterna-
tive for commercial tomographic image reconstruc-
tion methods. In this paper the iterative methods have
been studied and results show that they have potential
to performed better in various situations, especially
when projection data are not fully available (Ander-
sen, 1989). In addition, most of the papers describe
the behaviour of iterative algorithms by using phan-
tom data only (Mueller et al., 1999) without applying
to clinical patient measurement. In our work, compar-
ison of the CBCT iterative algorithms (ART (Gordon
et al., 1970) and SIRT (Gilbert, 1972)) implemented
in the Multi-Instrument Data Analysis System (MI-
DAS) (Mitchell and Spencer, 2003) tomography soft-
ware are presented by applying to phantom and clin-
ical data. Convergence rate, edge recovery, compu-
tational time and quality of the image are the main
criteria for considerations. Results are presented with
the image reconstructed from full data sets of CBCT
projection data using iterative algorithms (ART and
SIRT). They are compared in terms of the criteria
mentioned while a FDK image from the same system
is used as a reference.
2 THE CBCT SYSTEM AND DATA
In this study, the measured projection data were
provided by North Western Medical Physics at The
Christie hospital in Manchester. A ’RANDO’ anthro-
pomorphic head phantom
1
was scanned to produce
360 X-ray projection images, approximately evenly
spaced over an angular range of -100 to +100 de-
grees. Images were acquired at 100kV, 10mA and
10ms per projection, with total imaging dose of ap-
proximately 1.5mGy. Each projection image contains
512x512 pixels of dimension 0.8x0.8mm. Figure 1
shows the imaging system used in this study.
Using the full 360 projection data set a 3D re-
construction of 256x256x256 voxels with resolution
1mm in each direction was produced using iterative
1
The Phantom Laboratory, Salem, NY, USA.
550
Qiu W., Soleimani M., N. Mitchell C., Marchant T. and Moore C. (2010).
ITERATIVE IMAGE RECONSTRUCTION METHODS IN CONE BEAM CT APPLIED TO PHANTOM AND CLINICAL DATA.
In Proceedings of the International Conference on Computer Vision Theory and Applications, pages 550-553
DOI: 10.5220/0002892005500553
Copyright
c
SciTePress