eprintid: 10130687
rev_number: 18
eprint_status: archive
userid: 608
dir: disk0/10/13/06/87
datestamp: 2021-07-08 15:19:33
lastmod: 2021-10-21 23:18:11
status_changed: 2021-07-08 15:19:33
type: article
metadata_visibility: show
creators_name: Burger, M
creators_name: Hauptmann, A
creators_name: Helin, T
creators_name: Hyvonen, N
creators_name: Puska, JP
title: Sequentially optimized projections in x-ray imaging *
ispublished: pub
divisions: UCL
divisions: B04
divisions: C05
divisions: F48
keywords: Science & Technology, Physical Sciences, Mathematics, Applied, Physics, Mathematical, Mathematics, Physics, x-ray tomography, parallel beam tomography, optimal projections, Bayesian experimental design, A-optimality, D-optimality, sequential optimization, OPTIMAL EXPERIMENTAL-DESIGN, BAYESIAN EXPERIMENTAL-DESIGN, A-OPTIMAL DESIGN, INVERSE PROBLEMS
note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
abstract: This work applies Bayesian experimental design to selecting optimal projection
geometries in (discretized) parallel beam X-ray tomography assuming the prior and the additive
noise are Gaussian. The introduced greedy exhaustive optimization algorithm proceeds sequentially,
with the posterior distribution corresponding to the previous projections serving as the prior for
determining the design parameters, i.e. the imaging angle and the lateral position of the sourcereceiver pair, for the next one. The algorithm allows redefining the region of interest after each
projection as well as adapting parameters in the (original) prior to the measured data. Both A and
D-optimality are considered, with emphasis on efficient evaluation of the corresponding objective
functions. Two-dimensional numerical experiments demonstrate the functionality of the approach.
date: 2021-07-01
publisher: IOP PUBLISHING LTD
official_url: http://dx.doi.org/10.1088/1361-6420/ac01a4
oa_status: green
full_text_type: other
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1794122
doi: 10.1088/1361-6420/ac01a4
lyricists_name: Hauptmann, Andreas
lyricists_id: AHAUP49
actors_name: Hauptmann, Andreas
actors_id: AHAUP49
actors_role: owner
full_text_status: public
publication: Inverse Problems
volume: 37
number: 7
article_number: 075006
pages: 25
citation:        Burger, M;    Hauptmann, A;    Helin, T;    Hyvonen, N;    Puska, JP;      (2021)    Sequentially optimized projections in x-ray imaging *.                   Inverse Problems , 37  (7)    , Article 075006.  10.1088/1361-6420/ac01a4 <https://doi.org/10.1088/1361-6420%2Fac01a4>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10130687/1/2006.12579v1.pdf