Open AccessWide-field fluorescence molecular tomography with compressive sensing based preconditioning
Author(s) -
Ru Yao,
Qi Pian,
Xavier Intes
Publication year - 2015
Publication title -
biomedical optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.362
H-Index - 86
ISSN - 2156-7085
DOI - 10.1364/boe.6.004887
Subject(s) - compressed sensing , diffuse optical imaging , tomography , inverse problem , imaging phantom , computer science , tomographic reconstruction , iterative reconstruction , optical tomography , experimental data , optics , biomedical engineering , computer vision , artificial intelligence , physics , mathematics , medicine , mathematical analysis , statistics
Wide-field optical tomography based on structured light illumination and detection strategies enables efficient tomographic imaging of large tissues at very fast acquisition speeds. However, the optical inverse problem based on such instrumental approach is still ill-conditioned. Herein, we investigate the benefit of employing compressive sensing-based preconditioning to wide-field structured illumination and detection approaches. We assess the performances of Fluorescence Molecular Tomography (FMT) when using such preconditioning methods both in silico and with experimental data. Additionally, we demonstrate that such methodology could be used to select the subset of patterns that provides optimal reconstruction performances. Lastly, we compare preconditioning data collected using a normal base that offers good experimental SNR against that directly acquired with optimal designed base. An experimental phantom study is provided to validate the proposed technique.