Reduction of the scanning time by total variation minimization reconstruction for X-ray tomography in a SEM

Total variation minimization is applied to the particular case of X-ray tomography in a scanning electron microscope. To prove the efficiency of this reconstruction method, noise-free and noisy data based on the Shepp & Logan phantom have been simulated. These simulations confirm that Total variation minimization-reconstruction algorithm better manages data containing low number of projections with respect to simultaneous iterative reconstruction technique or filtered backprojection, even in the presence of noise. The algorithm has been applied to real data sets, with a low angular sampling and a high level of noise. Two samples containing micro-interconnections have been analyzed and 3D reconstructions show that Total variation minimization-based algorithm performs well even with 60 projections in order to properly recover a 500 nm diameter void inside a copper interconnection.