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Enhanced diffuse optical tomographic reconstruction using concurrent ultrasound information
Author(s) -
Giuseppe Di Sciacca,
Laura Di Sieno,
Andrea Farina,
Pranav Lanka,
Elena Venturini,
Pietro Panizza,
Alberto Dalla Mora,
Antonio Pifferi,
Paola Taroni,
Simon Arridge
Publication year - 2021
Publication title -
philosophical transactions of the royal society a mathematical physical and engineering sciences
Language(s) - English
Resource type - Journals
eISSN - 1471-2962
pISSN - 1364-503X
DOI - 10.1098/rsta.2020.0195
Subject(s) - computer science , diffuse optical imaging , modality (human–computer interaction) , tomographic reconstruction , artificial intelligence , iterative reconstruction , computer vision , tomography , regularization (linguistics) , optics , physics
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’.

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