In vivo imaging of small animals is of wide interest to the biomedical community studying biological disease and developmental processes. However, optical imaging deep in tissue is severely limited by light scattering, posing restrictions on the imaging depth, image contrast, and spatial resolution. We demonstrate optical coherence projection tomography (OCPT) as a fast three-dimensional optical imaging technique for ballistic, non-scattered light, deep-tissue imaging. OCPT is based on a novel scanning transmission sample arm to rapidly measure ballistic light projections of amplitude and phase through thick biological tissues. We demonstrate the strength of OCPT by imaging an adult zebrafish in a total volume of 1000 mm³ acquired in 24 min. We achieve an unprecedented imaging depth of 4 mm in biological tissue without using optical clearing (up to 27 mean free paths of photon transport). A new way of analyzing optical tomographic imaging depth is demonstrated and applied to OCPT. It shows that the strong light scattering suppression in OCPT is pivotal to reach the SNR limited imaging depth. OCPT allows for a full quantitative assessment of tissue parameters, which is demonstrated by quantifying the attenuation coefficient, refractive index, surface area, and volume of various organs deep inside the zebrafish. Our work opens up the way for longitudinal in vivo small animal studies from the larval to the adult stages.

We present a comparison of image reconstruction techniques for optical projection tomography. We compare conventional filtered back projection, sinogram filtering using the frequency–distance relationship (FDR), image deconvolution, and 2D point-spread-function-based iterative reconstruction. The latter three methods aim to remove the spatial blurring in the reconstructed image originating from the limited depth of field caused by the point spread function of the imaging system. The methods are compared based on simulated data, experimental optical projection tomography data of single fluorescent beads, and high-resolution optical projection tomography imaging of an entire zebrafish larva. We demonstrate that the FDR method performs poorly on data acquired with high numerical aperture optical imaging systems. We show that the deconvolution technique performs best on highly sparse data with low signal-to-noise ratio. The point-spread-function-based reconstruction method is superior for nonsparse objects and data of high signal-to-noise ratio.

We present a frequency domain analysis of the image resolution of optical tomography systems. The result of our analysis is a description of the spatially-variant resolution in optical tomographic image after reconstruction as a function of the properties of the imaging system geometry. We validate our model using optical projection tomography (OPT) measurements of fluorescent beads embedded in agarose gel. Our model correctly describes both the radial and tangential resolution of the measured images. In addition, we present a correction of the tomographic images for the spatially-varying resolution using a deconvolution algorithm. The resulting corrected tomographic reconstruction shows a homogeneous and isotropic pixel-limited resolution across the entire image. Our method is applied to OPT measurements of a zebrafish, showing improved resolution. Aside from allowing image correction and providing a resolution measure for OPT systems, our model provides a powerful tool for the design of optical tomographic systems.