Tomographic system design

Non-contact in vivo optical imaging systems purposely designed for bioluminescence and fluorescence molecular imaging (BLI, FMI) in small animals employing lens based cameras have become standard in preclinical laboratories. Such instruments comprise planar imaging systems that acquire two-dimensional (2D) images of a three-dimensional (3D) in vivo emission flux. When performing planar light emission imaging on complex surface geometries local emission ray intensities as well as spatial distribution thereof of the induced emission flux vary depending on alterations of camera position and angle with respect to the animal's surface. While respective measurement fluctuations could be minimized by detecting light rays orthogonally to surface points, such is impossible to achieve with a singular whole-body 2D light projection.

To address the problem of measuring in vivo emission light flux exiting the hull of a 3D object while preserving and estimating its a priori unknown 3D boundary space we report on the development and first simulation results of a plenoptic imaging system purposely designed for in vivo BLI and FMI application. Due to a multitude of arbitrarily positionable integrated laser diode light sources imposing point as well as bright-field illumination patterns, the system is able to perform multispectral fluorescence mediated tomography (FMT) and diffision optical tomography (DOT) without the exigency of a complementary imaging procedure for surface detection.

A plenoptic imaging system for preclinical in vivo imaging application has been developed (figure left). When imaging a three-dimensional (3D) object from six plenoptic camera positions, corresponding raw plenoptic data under bright-field illumination are shown. Acquisition setup and data used from a simulation study: Imaging system consisting of 6 plenoptic cameras with sensitive areas of 25mm× 50 mm, each, with nearly orthographic projections; there are (retractable) diffuse fiber line sources of detector length for object illumination located in the intermediary spaces between light detectors (top). The segmented volume of a reconstructed x-ray CT mouse data set is used as identified input (middle). Resulting raw plenoptic camera data as detected from 6 projection angles around 360° (bottom).

Computational mathematics

There are multiple imaging strategies involved in computational imaging. Here, surface reconstruction from multiview projection plenoptic image data is described (reference). The technique is adapted for in vivo small animal imaging, specifically imaging of nude mouse, and does not require an additional imaging step (e.g. be means of a secondary structural modality) or additional hardware (e.g. laser scanning approaches). Any potential point within the field-of-view (FOV) is evaluated by a proposed photo-consistency measure utilizing sensor image light information as provided by elemental images (EI's). As the superposition of adjacent EI's yields complementary information for any point within the FOV the three dimensional (3D) surface of the imaged object is estimated by a graph-cuts based method through global energy minimization. The proposed surface reconstruction is evaluated on simulated MLA-D data incorporating a reconstructed mouse data volume as acquired by X-ray CT. Compared to a previously presented back-projection based surface reconstruction method the proposed technique yields a significantly lower error rate. Moreover while the back-projection based method may not be able to resolve concave areas, the novel approach does. Our results further indicate that the proposed method achieves high accuracy at a low number of projections.

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