CUED Publications database

Bayesian inference for multidimensional NMR image reconstruction

Yoon, JW and Godsill, SJ (2006) Bayesian inference for multidimensional NMR image reconstruction. European Signal Processing Conference. ISSN 2219-5491

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Reconstruction of an image from a set of projections has been adapted to generate multidimensional nuclear magnetic resonance (NMR) spectra, which have discrete features that are relatively sparsely distributed in space. For this reason, a reliable reconstruction can be made from a small number of projections. This new concept is called Projection Reconstruction NMR (PR-NMR). In this paper, multidimensional NMR spectra are reconstructed by Reversible Jump Markov Chain Monte Carlo (RJMCMC). This statistical method generates samples under the assumption that each peak consists of a small number of parameters: position of peak centres, peak amplitude, and peak width. In order to find the number of peaks and shape, RJMCMC has several moves: birth, death, merge, split, and invariant updating. The reconstruction schemes are tested on a set of six projections derived from the three-dimensional 700 MHz HNCO spectrum of a protein HasA.

Item Type: Article
Divisions: Div F > Signal Processing and Communications
Depositing User: Unnamed user with email
Date Deposited: 17 Jul 2017 19:36
Last Modified: 22 Oct 2019 05:52