DMCA
Statistical inversion for medical X-ray tomography with few radiographs II: Application to dental radiology,” Phys (2003)
| Venue: | Med. Biol |
| Citations: | 28 - 9 self |
BibTeX
@ARTICLE{Siltanen03statisticalinversion,
author = {S Siltanen and V Kolehmainen and S Järvenpää and J P Kaipio and M Lassas and J Pirttilä and E Somersalo},
title = {Statistical inversion for medical X-ray tomography with few radiographs II: Application to dental radiology,” Phys},
journal = {Med. Biol},
year = {2003},
volume = {48},
pages = {1437--1463}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
Abstract. In X-ray tomography, the structure of a three dimensional body is reconstructed from a collection of projection images of the body. Medical CT imaging does this using an extensive set of projections from all around the body. However, in many practical imaging situations only a small number of truncated projections is available from a limited angle of view. Three dimensional imaging using such data is complicated for two reasons: (i) Typically, sparse projection data does not contain sufficient information to completely describe the 3-D body, and (ii) Traditional CT reconstruction algorithms, such as filtered backprojection, do not work well when applied to few irregularly spaced projections. Concerning (i), existing results about the information content of sparse projection data are reviewed and discussed. Concerning (ii), it is shown how Bayesian inversion methods can be used to incorporate a priori information into the reconstruction method, leading to improved image quality over traditional methods. Based on the discussion, a low-dose three-dimensional X-ray imaging modality is described. Submitted to: Phys. Med. Biol. 1.
Keyphrases
dental radiology statistical inversion radiograph ii medical x-ray tomography sparse projection data low-dose three-dimensional x-ray imaging modality filtered backprojection dimensional body projection image sufficient information priori information information content traditional ct reconstruction algorithm truncated projection image quality x-ray tomography 3-d body limited angle traditional method medical ct imaging small number bayesian inversion method reconstruction method extensive set many practical imaging situation
