Reconstruction of a yeast cell from X-ray diffraction data.
Details are provided of the algorithm used for the reconstruction of yeast cell images in the recent demonstration of diffraction microscopy by Shapiro, Thibault, Beetz, Elser, Howells, Jacobsen, Kirz, Lima, Miao, Nieman & Sayre [Proc. Natl Acad. Sci. USA (2005), 102, 15343-15346]. Two refinements of the iterative constraint-based scheme are developed to address the current experimental realities of this imaging technique, which include missing central data and noise. A constrained power operator is defined whose eigenmodes allow the identification of a small number of degrees of freedom in the reconstruction that are negligibly constrained as a result of the missing data. To achieve reproducibility in the algorithm's output, a special intervention is required for these modes. Weak incompatibility of the constraints caused by noise in both direct and Fourier space leads to residual phase fluctuations. This problem is addressed by supplementing the algorithm with an averaging method. The effect of averaging may be interpreted in terms of an effective modulation transfer function, as used in optics, to quantify the resolution. The reconstruction details are prefaced with simulations of wave propagation through a model yeast cell. These show that the yeast cell is a strong-phase-contrast object for the conditions in the experiment.
Thibault
Pierre
P
Department of Physics, Cornell University, Ithaca, NY 14853-2501, USA.
Elser
Veit
V
Jacobsen
Chris
C
Shapiro
David
D
Sayre
David
D
D000465:Algorithms; D055592:Biophysical Phenomena; D001703:Biophysics; D005583:Fourier Analysis; D007091:Image Processing, Computer-Assisted; D008853:Microscopy / Q000379:methods / Q000706:statistics & numerical data; D008954:Models, Biological; D012441:Saccharomyces cerevisiae / Q000166:cytology*; D014961:X-Ray Diffraction / Q000379:methods* / Q000706:statistics & numerical data