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An adaptive scheme for diffuse-optical tomography based on combined structured-light illumination and single-pixel camera detection

Farina, A; Betcke, M; Bassi, A; Valentini, G; Arridge, S; D'Andrea, C; (2019) An adaptive scheme for diffuse-optical tomography based on combined structured-light illumination and single-pixel camera detection. In: Dehghani, H and Wabnitz, H, (eds.) Diffuse Optical Spectroscopy and Imaging VII. SPIE: Munich, Germany. Green open access

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Abstract

Diffuse Optical Tomography (DOT) is a tool for 3D reconstruction of absorption and scattering inside a tissue. Typically, this method requires a dense distribution of sources and detectors, thus hampering the possibility of fully exploring a time-resolved detection. Recently, techniques based on structured-light illumination and compressing detection have been developed, opening the possibility of fully exploiting a source/detector spatial modulation for compression at the measurement stage. Here we propose a combined Continuous-Wave (CW) and time-domain (TD) adaptive scheme based on the singular-value decomposition (SVD) for optimal-patterns calculation. Patterns are firstly computed based on a fast acquisition via a CCD, and consequently projected for time-resolved measurements.

Type: Proceedings paper
Title: An adaptive scheme for diffuse-optical tomography based on combined structured-light illumination and single-pixel camera detection
Event: European Conferences on Biomedical Optics, 2019
Open access status: An open access version is available from UCL Discovery
DOI: 10.1117/12.2527689
Publisher version: https://doi.org/10.1117/12.2527689
Language: English
Additional information: This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions.
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/10089136
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