2006
DOI: 10.1109/tmi.2005.862206
|View full text |Cite
|
Sign up to set email alerts
|

Wavelet-based reconstruction for limited-angle X-ray tomography

Abstract: The aim of X-ray tomography is to reconstruct an unknown physical body from a collection of projection images. When the projection images are only available from a limited angle of view, the reconstruction problem is a severely ill-posed inverse problem. Statistical inversion allows stable solution of the limited-angle tomography problem by complementing the measurement data by a priori information. In this work, the unknown attenuation distribution inside the body is represented as a wavelet expansion, and a … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1

Citation Types

0
75
0

Year Published

2008
2008
2017
2017

Publication Types

Select...
7
3

Relationship

0
10

Authors

Journals

citations
Cited by 150 publications
(80 citation statements)
references
References 35 publications
0
75
0
Order By: Relevance
“…This regularity information can be used for example in denoising, classification, or re-construction of signals [16,19,21]. However, due to its isotropic nature, wavelets are not optimal for analyzing anisotropic features like edges.…”
Section: Introductionmentioning
confidence: 99%
“…This regularity information can be used for example in denoising, classification, or re-construction of signals [16,19,21]. However, due to its isotropic nature, wavelets are not optimal for analyzing anisotropic features like edges.…”
Section: Introductionmentioning
confidence: 99%
“…This performance resembles the characteristics of limited projection x-ray tomosynthesis over x-ray CT, but in the diffusive photon regime. 56,57 The use of prior information can reduce the ill-posed nature of the limited-projection-angle FMT inverse problem. The use of priors has shown to improve the imaging performance of 360 deg projection FMT, but it is even more essential for limited-projection-angle FMT, since reducing the information contained in the data collected increases the ill-posed nature of the reconstruction problem.…”
Section: Discussionmentioning
confidence: 99%
“…dim E h f ). These spectra are useful in denoising, classification, or reconstruction of signals (see [22,23,35]). Definition 1.1.…”
Section: Introductionmentioning
confidence: 99%