Authors:
Hmida Rojbani
1
;
Étienne Baudrier
2
;
Benoît Naegel
2
;
Loïc Mazo
2
and
Atef Hamouda
3
Affiliations:
1
University of Strasbourg and University El-Manar, France
;
2
University of Strasbourg, France
;
3
University El-Manar, Tunisia
Keyword(s):
Electron Tomography, 3D Structures, Tilt Angles, Angular Uncertainty, Optimization, Conjugate Gradient.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Early and Biologically-Inspired Vision
;
Image and Video Analysis
;
Image Enhancement and Restoration
;
Image Formation and Preprocessing
;
Medical Image Applications
Abstract:
In the field of cryo-electron tomography (cryo-ET), numerous approaches have been proposed to tackle the
difficulties of the three-dimensional reconstruction problem. And that, in order to cope with (1) the missing
and noisy data from the collected projections, (2) errors in projection images due to acquisition problems, (3)
the capacity of processing large data sets and parameterizing the contrast function of the electron microscopy.
In this paper, we present a novel approach for dealing with angular uncertainty in cryo-ET. To accomplish this
task we propose a cost function and with the use of the nonlinear version of the optimization algorithm called
Conjugate Gradient, we minimize it. We test the efficiency of our algorithm with both simulated and real data.