Automated motion correction for in vivo optical projection tomography.

In in vivo optical projection tomography (OPT), object motion will significantly reduce the quality and resolution of the reconstructed image. Based on the well-known Helgason-Ludwig consistency condition (HLCC), we propose a novel method for motion correction in OPT under parallel beam illumination. The method estimates object motion from projection data directly and does not require any other additional information, which results in a straightforward implementation.

Microscopic optical projection tomography in vivo.

We describe a versatile optical projection tomography system for rapid three-dimensional imaging of microscopic specimens in vivo. Our tomographic setup eliminates the in xy and z strongly asymmetric resolution, resulting from optical sectioning in conventional confocal microscopy. It allows for robust, high resolution fluorescence as well as absorption imaging of live transparent invertebrate animals such as C.

Improved reconstructions and generalized filtered back projection for optical projection tomography.

Optical projection tomography (OPT) is a noninvasive imaging technique that enables imaging of small specimens (<1 cm), such as organs or animals in early developmental stages. In this paper, we present a set of computational methods that can be applied to the acquired data sets in order to correct for (a) unknown background or illumination intensity distributions over the field of view, (b) intensity spikes in single CCD pixels (so-called "hot pixels"), and (c) refractive index mismatch between the media in which the specimens are embedded and the environment. We have tested these correction methods using a variety of samples and present results obtained from Parhyale hawaiensis embedded in glycerol and in sea water.

Correction for specimen movement and rotation errors for in-vivo Optical Projection Tomography.

The application of optical projection tomography to in-vivo experiments is limited by specimen movement during the acquisition. We present a set of mathematical correction methods applied to the acquired data stacks to correct for movement in both directions of the image plane. These methods have been applied to correct experimental data taken from in-vivo optical projection tomography experiments in Caenorhabditis elegans.