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Bootstrap-Optimised Regularised Image Reconstruction for Emission Tomography

Authors: Andrew J. Reader; Sam Ellis;

Bootstrap-Optimised Regularised Image Reconstruction for Emission Tomography

Abstract

Supporting data and MATLAB code for the paper: A. J. Reader and S. Ellis, "Bootstrap-Optimised Regularised Image Reconstruction for Emission Tomography," in IEEE Transactions on Medical Imaging (2020) DOI: 10.1109/TMI.2019.2956878 Instructions for use (tested on MATLAB R2017a): - unzip the file bootstrap_optimised_PET_image_reconstruction.zip Dependencies - add the utils directory to your path before running the scripts. Figures - there is a directory for each figure, not including those figures which do not contain experimental results. Each directory contains a .m script file and a .mat data file. Running the .m file produces the figure roughly as it appears in the manuscript. Independent exploration of the data can be performed if desired. Sample code - Running the example.m file will perform example 2D reconstructions with MLEM, bootstrap optimised guided quadratic MAPEM, and bootstrap optimised unweighted quadratic MAPEM. The reconstruction code is contained in the @reconClass folder. This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) [EP/M020142/1]; and the Wellcome/EPSRC Centre for Medical Engineering [WT 203148/Z/16/Z].

Country
United Kingdom
Keywords

inverse problems, Phantoms, Imaging, hyperparameter selection, Article, 004, 620, emission tomography, Positron-Emission Tomography, Image reconstruction, regularisation, Image Processing, Computer-Assisted, Tomography, X-Ray Computed, Algorithms, bootstrap methods

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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