PyHST2: an hybrid distributed code for high speed tomographic reconstruction with iterative reconstruction and a priori knowledge capabilities

Alessandro Mirone (1) , Emmanuelle Gouillart (2) , Emmanuel Brun (3) , Paul Tafforeau (1) , Jérome Kieffer (1)

1 ESRF - European Synchrotron Radiation Facility
2 SVI - Surface du Verre et Interfaces
3 IUSTI - Institut universitaire des systèmes thermiques industriels

We present the PyHST2 code which is in service at ESRF for phase-contrast and absorption tomography. This code has been engineered to sustain the high data flow typical of the third generation synchrotron facilities (10 terabytes per experiment) by adopting a distributed and pipelined architecture. The code implements, beside a default filtered backprojection reconstruction, iterative reconstruction techniques with a-priori knowledge. These latter are used to improve the reconstruction quality or in order to reduce the required data volume and reach a given quality goal. The implemented a-priori knowledge techniques are based on the total variation penalisation and a new recently found convex functional which is based on overlapping patches. We give details of the different methods and their implementations while the code is distributed under free license. We provide methods for estimating, in the absence of ground-truth data, the optimal parameters values for a-priori techniques.

Domaines: Analyse numérique [cs.NA]

Alessandro Mirone, Emmanuelle Gouillart, Emmanuel Brun, Paul Tafforeau, Jérome Kieffer. PyHST2: an hybrid distributed code for high speed tomographic reconstruction with iterative reconstruction and a priori knowledge capabilities. Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms, 2014, 324, pp.41. ⟨hal-01071551⟩