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Synchromodal emission imaging

© dkfz.de

To enable what we call synchromodal optical imaging we invented the first plenoptic camera for diagnostic research that not only creates three-dimensional (illumination and fluence) projections of the imaged subject, but can also be integrated and used with PET and MRI (reference). The world's first simultaneously acquired [18F]FDG PET - pVEGF Luc BLI plenoptic image is shown in the left figure (top: experimental plenoptic system integrated into a Siemens Inveon PET for simultaneous data acquisition, bottom: fused PET and OI data (reference)).

A complete instrumentation and mathematical framework for preclinical plenoptic imaging (POI) is developed in which optical data is acquired by means of a microlens array (MLA) based light detector (MLA-D). The MLA-D has been developed to enable unique POI, especially in synchromodal operation with secondary imaging modalities such as PET or MRI. An MLA-D consists of a (large-area) photon sensor array, a matched MLA for field-of-view definition, and a septum mask of specific geometry made of anodized aluminum that is positioned between the sensor and the MLA to suppresses light cross-talk and to shield the sensor's radiofrequency interference signal (essential when used inside an MRI system). The software framework, while freely parameterizable for any MLA-D, is tailored towards a POI prototype system for preclinical synchromodal imaging application comprising a multitude of cylindrically assembled, gantry-mounted, simultaneously operating MLA-D's. When used in synchromodal operation, reconstructed tomographic volume data can be used for co-modal image fusion and also as a prior for estimating the imaged object's 3D surface by means of gradient vector flow. Superimposed planar or surface-aligned inverse mapping can be performed to estimate and to fuse the emission light map with the boundary of the imaged object. Triangulation and subsequent optical reconstruction can be performed to estimate the internal three-dimensional emission light distribution. The framework is susceptible to a number of variables controlling convergence and computational speed.

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