Comparison of reconstruction methods for optical projection tomography with sparse angle projections

Optical projection tomography (OPT) is a three-dimensional (3D) imaging technique for biological samples, capable of visualizing tissues, embryos, and organs within 1mm to 10 mm scale. Filtered back projection (FBP) is an extensively used 3D reconstruction algorithm for OPT with dense sampling data from all view angles. In-vivo OPT can reduce the inspection time by using equally-spaced sparse angle projections to mitigate the side effects of phototoxicity and anesthetics. This work compares the reconstruction results of the sparse-angle OPT using different algorithms, including the FBP algorithm and two kinds of compressive sensing (CS) algorithms with different projection numbers. We also build up a testbed of OPT to verify these algorithms using experimental data. It shows that the CS algorithms result in reconstructed images with fewer artifacts compared to the FBP algorithm. Especially, the advantage of CS algorithms over FBP algorithm becomes more obvious as the projection number is reduced.