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This article describes a novel non-contact fluorescence optical tomography scheme which utilizes multiple area illumination patterns, to reduce the ill-posedness of the inverse problem involved in recovering interior fluorescence yield distributions in biological tissue from boundary fluorescence measurements. The image reconstruction is posed as an optimization problem which seeks a tissue optical property distribution minimizing, for all illumination patterns simultaneously, a regularized difference between the observed boundary measurements of light distribution, and the boundary measurements predicted from a physical model. Multiple excitation source illumination patterns are described by line and Gaussian sources scanning the simulated tissue phantom surface and by employing diffractive optics-generated patterns. Multiple measurement data sets generated by scanning excitation sources are processed simultaneously to generate the interior fluorescence distribution in tissue by implementing the fluorescence tomography algorithm in a parallel framework suitable for multiprocessor computers. Image reconstructions for single and multiple fluorescent targets (5mm diameter) embedded in a 512ml simulated tissue phantom are demonstrated, with depths of the fluorescent targets from the illumination plane between 1cm to 2cm. We show both qualitative and quantitative improvements of our algorithm over reconstructions from only a single measurement.

Non-contact fluorescence optical tomography with scanning patterned illumination