Abstract
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.
Highlights
Fluorescence Molecular Tomography (FMT) has known a rapid development over the last decade and half [1]
Both illumination and detection masks are jointly employed, leading to a tomographic “single pixel” system. We successfully extended this approach to time-resolved FMT by implementing time-resolved wide-field structured light illumination and generating detection patterns via spatial integration of gated ICCD data sets
We demonstrated that the spatial integration did not compromise temporal data sets and that quantitative accurate optical tomography was feasible with performance similar to punctual optode strategies for absorptive inclusions [3]
Summary
Fluorescence Molecular Tomography (FMT) has known a rapid development over the last decade and half [1]. Belanger et al [2] demonstrated that diffuse optical tomography based on a double light modulator architecture was achievable at very high speed In this implementation, both illumination and detection masks are jointly employed, leading to a tomographic “single pixel” system. Both illumination and detection masks are jointly employed, leading to a tomographic “single pixel” system We successfully extended this approach to time-resolved FMT by implementing time-resolved wide-field structured light illumination and generating detection patterns via spatial integration of gated ICCD data sets. We have extended the methodology to hyperspectral time-resolved imaging by coupling the double light modulator design with a time-resolved spectrophotometer [8] This implementation enables the acquisition of dense 4D data cubes for FMT (2D spatial, temporal and spectral). We compare results when using the preconditioning method post-hoc on experimental data from our bar pattern base with that directly collected from the optimal base
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