A simple derivation and analysis of a helical cone beam tomographic algorithm for long object imaging via a novel definition of region of interest. Phys Med Biol 2004 Jan 21;49(2):205-25
Date
04/16/2004Pubmed ID
15083667DOI
10.1088/0031-9155/49/2/003Scopus ID
2-s2.0-0942266356 (requires institutional sign-in at Scopus site) 4 CitationsAbstract
We derive and analyse a simple algorithm first proposed by Kudo et al (2001 Proc. 2001 Meeting on Fully 3D Image Reconstruction in Radiology and Nuclear Medicine (Pacific Grove, CA) pp 7-10) for long object imaging from truncated helical cone beam data via a novel definition of region of interest (ROI). Our approach is based on the theory of short object imaging by Kudo et al (1998 Phys. Med. Biol. 43 2885-909). One of the key findings in their work is that filtering of the truncated projection can be divided into two parts: one, finite in the axial direction, results from ramp filtering the data within the Tam window. The other, infinite in the z direction, results from unbounded filtering of ray sums over PI lines only. We show that for an ROI defined by PI lines emanating from the initial and final source positions on a helical segment, the boundary data which would otherwise contaminate the reconstruction of the ROI can be completely excluded. This novel definition of the ROI leads to a simple algorithm for long object imaging. The overscan of the algorithm is analytically calculated and it is the same as that of the zero boundary method. The reconstructed ROI can be divided into two regions: one is minimally contaminated by the portion outside the ROI, while the other is reconstructed free of contamination. We validate the algorithm with a 3D Shepp-Logan phantom and a disc phantom.
Author List
Hu J, Tam K, Johnson RHAuthor
Roger H. Johnson PhD Associate Professor in the Biophysics department at Medical College of WisconsinMESH terms used to index this publication - Major topics in bold
AlgorithmsComputer Simulation
Image Processing, Computer-Assisted
Models, Theoretical
Phantoms, Imaging
Tomography Scanners, X-Ray Computed
Tomography, X-Ray Computed