Bayesian inversion method for 3D dental X-ray imaging

被引：8
作者：
Kolehmainen V. [1 ]
Vanne A. [1 ]
Siltanen S. [4 ]
Järvenpää S. [2 ]
Kaipio J.P. [1 ]
Lassas M. [2 ]
Kalke M. [3 ]
机构：
[1] University of Kuopio, 70211 Kuopio
[2] Helsinki University of Technology, 02015 TKK
[3] PaloDEx Group, 04301 Tuusula
[4] Tampere University of Technology, 33101 Tampere
来源：
Elektrotechnik und Informationstechnik | 2007年 / 124卷 / 7-8期
基金：
芬兰科学院;
关键词：
Beowulf; Dental; Inverse problems; Parallel computing; X-ray tomography;
D O I：
10.1007/s00502-007-0450-7
中图分类号：
学科分类号：
摘要：
Diagnostic and operational tasks in dentistry require three-dimensional (3D) information about tissue. A novel type of low dose dental 3D X-ray imaging is considered. Given projection images taken from a few sparsely distributed directions using the dentist's regular X-ray equipment, the 3D X-ray attenuation function is reconstructed. This is an ill-posed inverse problem, and Bayesian inversion is a well suited framework for reconstruction from such incomplete data. The reconstruction problem is formulated in a well-posed probabilistic form in which a priori information is used to compensate for the incomplete data. A parallelized Bayesian method (implemented for a Beowulf cluster computer) for 3D reconstruction in dental radiology is presented (the method was originally presented in (Kolehmainen et al., 2006)). The prior model for dental structures consists of a weighted l 1 and total variation (TV)-prior together with the positivity prior. The inverse problem is stated as finding the maximum a posterior (MAP) estimate. The method is tested with in vivo patient data and shown to outperform the reference method (tomosynthesis). © 2007 Springer-Verlag.
引用
收藏
页码：248 / 253
页数：5
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