Optical Projection Tomography (OPT), the optical equivalent of x-ray computed tomography, reconstructs the 3D structure of a sample from a series of wide-field 2D projections acquired at different angles . OPT is used to map the optical attenuation and/or fluorescence distributions of intact transparent samples without the need for mechanical sectioning. While it is typically applied to chemically cleared samples, it can also be used to image inherently transparent or weakly scattering live organisms including adult zebrafish up to ~1cm in diameter .
When applying OPT to live samples it is important to minimise the data acquisition time while maximising the image quality in the presence of scattering. The former issue can be addressed using compressive sensing to reduce the number of projections required . Scattered light can be rejected using structured illumination , but this removes emission from regions the excitation modulation does not reach and reduces the available dynamic range. To address this, we have explored the rejection of scattered light by acquiring projections with parallel semi-confocal line illumination and detection in an approach we describe as slice-OPT (sl-OPT).
The impact of optical scattering can also be reduced by imaging at longer wavelengths . We are exploring OPT in the NIR 1&2 spectral windows. However, exotic array detectors, e.g. for short wave infrared light, are costly and so we are also developing a single pixel camera  approach. We will present our progress applying these techniques to 3D imaging of vasculature and tumour burden in live adult zebrafish.
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Samuel P. Davis, Sunil Kumar, Laura Wisniewski, Marie-Christine Ramel, Laurence Bugeon, Teresa Correia, Maggie Dallman, Simon Arridge, Paul Frankel, James McGinty, and PaulM. W. French, "Exploiting patterned illumination and detection in optical projection tomography (Conference Presentation)," Proc. SPIE 10883, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVI, 108830M (Presented at SPIE BiOS: February 06, 2019; Published: 4 March 2019); https://doi.org/10.1117/12.2508653.6008557197001.
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