Di Sciacca, G;
Di Sieno, L;
Farina, A;
Lanka, P;
Venturini, E;
Panizza, P;
Dalla Mora, A;
... Arridge, SR; + view all
(2021)
Enhanced diffuse optical tomographic reconstruction using concurrent ultrasound information.
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
, 379
(2204)
, Article 20200195. 10.1098/rsta.2020.0195.
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Abstract
Multimodal imaging is an active branch of research as it has the potential to improve common medical imaging techniques. Diffuse optical tomography (DOT) is an example of a low resolution, functional imaging modality that typically has very low resolution due to the ill-posedness of its underlying inverse problem. Combining the functional information of DOT with a high resolution structural imaging modality has been studied widely. In particular, the combination of DOT with ultrasound (US) could serve as a useful tool for clinicians for the formulation of accurate diagnosis of breast lesions. In this paper, we propose a novel method for US-guided DOT reconstruction using a portable time-domain measurement system. B-mode US imaging is used to retrieve morphological information on the probed tissues by means of a semi-automatical segmentation procedure based on active contour fitting. A two-dimensional to three-dimensional extrapolation procedure, based on the concept of distance transform, is then applied to generate a three-dimensional edge-weighting prior for the regularization of DOT. The reconstruction procedure has been tested on experimental data obtained on specifically designed dual-modality silicon phantoms. Results show a substantial quantification improvement upon the application of the implemented technique. This article is part of the theme issue ‘Synergistic tomographic image reconstruction: part 2’.
Type: | Article |
---|---|
Title: | Enhanced diffuse optical tomographic reconstruction using concurrent ultrasound information |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1098/rsta.2020.0195 |
Publisher version: | https://doi.org/10.1098/rsta.2020.0195 |
Language: | English |
Additional information: | © 2021 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/). |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
URI: | https://discovery.ucl.ac.uk/id/eprint/10131330 |




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