000207799 001__ 207799
000207799 005__ 20180317094117.0
000207799 0247_ $$2doi$$a10.5075/epfl-thesis-6621
000207799 02470 $$2urn$$aurn:nbn:ch:bel-epfl-thesis6621-1
000207799 02471 $$2nebis$$a10433889
000207799 037__ $$aTHESIS_LIB
000207799 041__ $$aeng
000207799 088__ $$a6621
000207799 245__ $$aHigh Performance Reconstruction Framework for Straight Ray Tomography$$bfrom Micro to Nano Resolution Imaging
000207799 269__ $$a2015
000207799 260__ $$aLausanne$$bEPFL$$c2015
000207799 336__ $$aTheses
000207799 502__ $$aProf. J.-Ph. Thiran (président) ;  Prof. M. Unser (directeur) ;   Prof. C. Oscar Sánchez Sorzano,   Prof. F. Peyrin,   Prof. D. Van De Ville (rapporteurs)
000207799 520__ $$aWe develop a high-performance scheme to reconstruct straight-ray tomographic scans. We preserve the quality of the state-of-the-art schemes typically found in traditional computed tomography but reduce the computational cost substantially. Our approach is based on 1) a rigorous discretization of the forward model using a generalized sampling scheme; 2) a variational formulation of the reconstruction problem; and 3) iterative reconstruction algorithms that use the alternating-direction method of multipliers. To improve the quality of the reconstruction, we take advantage of total-variation regularization and its higher-order variants. In addition, the prior information on the support and the positivity of the refractive index are both considered, which yields significant improvements. The two challenging applications to which we apply the methods of our framework are grating-based \mbox{x-ray} imaging (GI) and single-particle analysis (SPA). In the context of micro-resolution GI, three complementary characteristics are measured: the conventional absorption contrast, the differential phase contrast, and the small-angle scattering contrast. While these three measurements provide powerful insights on biological samples, up to now they were calling for a large-dose deposition which potentially was harming the specimens ({\textit{e.g.}}, in small-rodent scanners). As it turns out, we are able to preserve the image quality of filtered back-projection-type methods despite the fewer acquisition angles and the lower signal-to-noise ratio implied by a reduction in the total dose of {\textit{in-vivo}} grating interferometry. To achieve this, we first apply our reconstruction framework to differential phase-contrast imaging (DPCI). We then add Jacobian-type regularization to simultaneously reconstruct phase and absorption. The experimental results confirm the power of our method. This is a crucial step toward the deployment of DPCI in medicine and biology. Our algorithms have been implemented in the TOMCAT laboratory of the Paul Scherrer Institute. In the context of near-atomic-resolution SPA, we need to cope with hundreds or thousands of noisy projections of macromolecules onto different micrographs. Moreover, each projection has an unknown orientation and is blurred by some space-dependent point-spread function of the microscope. Consequently, the determination of the structure of a macromolecule involves not only a reconstruction task, but also the deconvolution of each projection image. We formulate this problem as a constrained regularized reconstruction. We are able to directly include the contrast transfer function in the system matrix without any extra computational cost. The experimental results suggest that our approach brings a significant improvement in the quality of the reconstruction. Our framework also provides an important step toward the application of SPA for the {\textit{de novo}} generation of macromolecular models. The corresponding algorithms have been implemented in Xmipp.
000207799 6531_ $$aDiscretization
000207799 6531_ $$avariational formulation
000207799 6531_ $$aiterative reconstruction
000207799 6531_ $$aalternating-direction method of multipliers
000207799 6531_ $$agrating-based x-ray imaging
000207799 6531_ $$asingle-particle analysis
000207799 6531_ $$aphase-contrast imaging
000207799 6531_ $$acomputed tomography
000207799 6531_ $$ahigh performance reconstruction
000207799 700__ $$0242492$$aNilchian, Masih$$g200177
000207799 720_2 $$0240182$$aUnser, Michaël$$edir.$$g115227
000207799 8564_ $$s51405405$$uhttps://infoscience.epfl.ch/record/207799/files/EPFL_TH6621.pdf$$yn/a$$zn/a
000207799 909CO $$ooai:infoscience.tind.io:207799$$pthesis-bn2018$$pSTI$$pthesis
000207799 909C0 $$0252054$$pLIB$$xU10347
000207799 917Z8 $$x108898
000207799 917Z8 $$x108898
000207799 917Z8 $$x108898
000207799 917Z8 $$x108898
000207799 918__ $$aSTI$$cIMT$$dEDEE
000207799 919__ $$aLIB
000207799 920__ $$a2015-5-11$$b2015
000207799 970__ $$a6621/THESES
000207799 973__ $$aEPFL$$sPUBLISHED
000207799 980__ $$aTHESIS