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Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

  • Editor: Gregory W. Faris
  • Vol. 5, Iss. 10 — Jul. 19, 2010
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Fresnel coherent diffraction tomography

C. T. Putkunz, M. A. Pfeifer, A. G. Peele, G. J. Williams, H. M. Quiney, B. Abbey, K. A. Nugent, and I. McNulty  »View Author Affiliations


Optics Express, Vol. 18, Issue 11, pp. 11746-11753 (2010)
http://dx.doi.org/10.1364/OE.18.011746


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Abstract

Tomographic coherent imaging requires the reconstruction of a series of two-dimensional projections of the object. We show that using the solution for the image of one projection as the starting point for the reconstruction of the next projection offers a reliable and rapid approach to the image reconstruction. The method is demonstrated on simulated and experimental data. This technique also simplifies reconstructions using data with curved incident wavefronts.

© 2010 Optical Society of America

1. Introduction

Coherent diffractive imaging (CDI), that inverts a far field x-ray diffraction pattern to obtain a quantitative image is now a viable and useful technique [1–4

1. H. Chapman, A. Barty, S. Marchesini, A. Noy, S. Hau-Riege, C. Cui, M. Howells, R. Rosen, H. He, J. Spence, U. Weierstall, T. Beetz, C. Jacobsen, and D. Shapiro, “High-resolution ab initio three-dimensional x-ray diffraction microscopy,” J. Opt. Soc. Am. A. 23, 1179–1200 (2006). [CrossRef]

]. At third generation synchrotron sources a rationale for this work lies in the promise of high resolution 3D microscopy for materials and biological samples. Since the first demonstration of CDI using x-rays [5

5. J. Miao, P. Charalambous, J. Kirz, and D. Sayre, “Extending the methodology of x-ray crystallography to allow imaging of micrometre-sized non-crystalline specimens,” Nature 400, 342–344 (1999). [CrossRef]

] the technique has been applied to various isolated materials samples [6–8

6. J. Miao, T. Ishikawa, B. Johnson, E. Anderson, B. Lai, and K. Hodgson, “High resolution 3d x-ray diffraction microscopy,” Phys. Rev. Lett. 89, 088303 (2002). [CrossRef] [PubMed]

], as well as de-hydrated [9–11

9. J. Miao, K. Hodgson, T. Ishikawa, C. Larabell, M. LeGros, and Y. Nishino, “Imaging whole escherichia coli bacteria by using single-particle x-ray diffraction,” Proc. Nat. Acad. Sci. USA 100, 110–112 (2003). [CrossRef] [PubMed]

] and hydrated biological specimens [12

12. E. Lima, L. Wiegart, P. Pernot, M. Howells, J. Timmins, F. Zontone, and A. Madsen, “Cryogenic x-ray diffraction microscopy for biological samples,” Phys. Rev. Lett. 103, - (2009). [CrossRef]

, 13

13. X. Huang, J. Nelson, J. Kirz, E. Lima, S. Marchesini, H. Miao, A. Neiman, D. Shapiro, J. Steinbrener, A. Stewart, J. Turner, and C. Jacobsen, “Soft x-ray diffraction microscopy of a frozen hydrated yeast cell,” Phys. Rev. Lett. 103, 198101 (2009). [CrossRef]

].

CDI uses iterative algorithms that recover the phase of the diffracted wavefield. A range of new algorithms continue to be developed [14

14. S. Marchesini, “A unified evaluation of iterative projection algorithms for phase retrieval,” Rev. Sci. Instrum. 78, 011301 (2007). [CrossRef] [PubMed]

]. A significant portion of this work is motivated by problems with stagnation, or the speed of the iterative solutions. Examples include algorithms such as hybrid input-output (HIO) [15

15. J. R. Fienup, “Phase retrieval algorithms: a comparison,” Appl. Opt. 21, 2758–2769 (1982). [CrossRef] [PubMed]

] and difference map (DM) [16

16. V. Elser, “Phase retrieval by iterated projections,” J. Opt. Soc. Am. A 20, 40–55 (2003). [CrossRef]

], which are argued to reduce the chance of stagnation by not strictly enforcing steepest descent [15

15. J. R. Fienup, “Phase retrieval algorithms: a comparison,” Appl. Opt. 21, 2758–2769 (1982). [CrossRef] [PubMed]

]. “Pytchographic” methods incorporating multiple diffraction data sets based on a translated illumination have also shown notable improvements in reconstruction quality [17

17. J. Rodenburg and H. Faulkner, “A phase retrieval algorithm for shifting illumination,” App. Phys. Lett. 85, 4795–4797 (2004). [CrossRef]

, 18

18. P. Thibault, M. Dierolf, A. Menzel, O. Bunk, C. David, and F. Pfeiffer, “High-resolution scanning x-ray diffraction microscopy,” Science 321, 379–382 (2008). [CrossRef] [PubMed]

].

The uniqueness of the recovered solution is also known to be compromised by certain pathological cases [19

19. R. Bates, “Uniqueness of solutions to two-dimensional fourier phase problems for localized and positive images,” Comput. Vision Graph. 25, 205–217 (1984). [CrossRef]

]. It has been shown that these problems can be ameliorated by use of sufficient phase structure in the illumination, often provided in the form of spherical curvature [20

20. K. Nugent, A. Peele, H. Chapman, and A. Mancuso, “Unique phase recovery for nonperiodic objects,” Phys. Rev. Lett. 91, 203902 (2003). [CrossRef] [PubMed]

]. In this case, the resulting far-field diffraction pattern must be treated in the Fresnel approximation [20–22

20. K. Nugent, A. Peele, H. Chapman, and A. Mancuso, “Unique phase recovery for nonperiodic objects,” Phys. Rev. Lett. 91, 203902 (2003). [CrossRef] [PubMed]

]. Experimental verification of this Fresnel coherent diffractive imaging (FCDI) approach has now been obtained [8

8. G. Williams, H. Quiney, B. Dhal, C. Tran, K. Nugent, A. Peele, D. Paterson, and M. de Jonge, “Fresnel coherent diffractive imaging,” Phys. Rev. Lett. 97, 025506 (2006). [CrossRef] [PubMed]

, 11

11. G. Williams, E. Hanssen, A. Peele, M. Pfeifer, J. Clark, B. Abbey, G. Cadenazzi, M. de Jonge, S. Vogt, L. Tilley, and K. Nugent, “High-resolution x-ray imaging of plasmodium falciparum-infected red blood cells,” Cytom. Part A 73A, 949–957 (2008). [CrossRef]

, 23–26

23. H. Quiney, A. Peele, Z. Cai, D. Paterson, and K. Nugent, “Diffractive imaging of highly focused x-ray fields,” Nat. Phys. 2, 101–104 (2006). [CrossRef]

].

In many experimental geometries, the complex exit surface wave from a sample obtained by CDI can be described as a projection through the sample [27

27. D. Paganin, Coherent X-Ray Optics (Oxford University Press, 2006). [CrossRef]

]. In this case the Fourier slice theorem [28

28. M. Born and E. Wolf, Principles of Optics: Electromagnetic Theory of Propagation, Interference and Diffraction of Light (7th Edition) (Cambridge University Press, 1999). [PubMed]

] can be used to calculate the 3D sample distribution from a series of angular projections.

2. Method

The iterative reconstruction algorithms we use are based on the original ideas of [15

15. J. R. Fienup, “Phase retrieval algorithms: a comparison,” Appl. Opt. 21, 2758–2769 (1982). [CrossRef] [PubMed]

, 30

30. R. W. Gerchberg and W. O. Saxton, “A pratical algorithm for the determination of phase from image and diffraction plane pictures,” Optik (Stuttgart) 35, 237–246 (1972).

], and have been usefully summarised elsewhere [14

14. S. Marchesini, “A unified evaluation of iterative projection algorithms for phase retrieval,” Rev. Sci. Instrum. 78, 011301 (2007). [CrossRef] [PubMed]

]. In this paper we use FCDI with error reduction (ER) [31

31. J. R. Fienup, “Reconstructions of an object from the modulus of its fourier transform,” Opt. Lett. 3, 27–29 (1978). [CrossRef] [PubMed]

], in which the illuminating field is used to define the object extent [24

24. B. Abbey, K. Nugent, G. Williams, J. Clark, A. Peele, M. Pfeifer, M. De Jonge, and I. McNulty, “Keyhole coherent diffractive imaging,” Nat. Phys. 4, 394–398 (2008). [CrossRef]

]. The iterative algorithm was run until a self consistent, or converged solution was obtained. This was quantified by the χ 2 between the simulated or measured data, I(ρd), and the squared amplitude of the current iterate, ∣ ψ^ (ρd)∣2:

χ2=ρd[ψ̂(ρd)I(ρd)]2ρdI(ρd),
(1)

where ρd is the detector coordinate. Specifically, convergence was defined to be when χ 2 between successive iterates differed by less than a defined fraction, F. Changes in experimental geometry, sample size, noise levels, and the defined support region can vary the χ 2. Here we used a convergence of F = 10−4 for the simulations and F = 10−3 for the experimental data.

Our method, which we term the “bootstrap” method, is as follows. Given a recovered transmission function for a neighbouring projection, T θθ, and the measured or simulated intensity at the detector, I θ, an initial estimate for the wavefield at the detector for the current projection, ψ̂θ, is calculated via:

ψ̂e(ρd)=ρsψ0(ρs)TθΔθeiπρs2λzDe2πiρsρddρs;and
(2)
ψ̂θ(ρd)=Iθ(ρd)ψ̂e(ρd)ψ̂e(ρd).
(3)

Here ρs and ρd are the 2D sample and detector coordinates respectively and ψ 0(ρs) is the illuminating beam in the sample plane. ψ̂e(ρd) is the initial estimate of the sample exit wavefield propagated to the detector using the Fresnel free space propagator [23

23. H. Quiney, A. Peele, Z. Cai, D. Paterson, and K. Nugent, “Diffractive imaging of highly focused x-ray fields,” Nat. Phys. 2, 101–104 (2006). [CrossRef]

] with a propagation distance of zD, and wavelength λ. This is then iterated on using the techniques of 2D FCDI [8

8. G. Williams, H. Quiney, B. Dhal, C. Tran, K. Nugent, A. Peele, D. Paterson, and M. de Jonge, “Fresnel coherent diffractive imaging,” Phys. Rev. Lett. 97, 025506 (2006). [CrossRef] [PubMed]

, 26

26. J. Clark, C. Putkunz, M. Pfeifer, A. Peele, G. Williams, B. Chen, K. Nugent, C. Hall, W. Fullagar, S. Kim, and I. McNulty, “Use of a complex constraint in coherent diffractive imaging,” Opt. Express 18, 1981–1993 (2010). [CrossRef] [PubMed]

].

The recovered complex exit surface wave is used to obtain the projection through the sample of both the decrement from unity of the real part of the refractive index, δ, and the imaginary part of the refractive index, β [32

32. J. Clark, G. Williams, H. Quiney, L. Whitehead, M. de Jonge, E. Hanssen, M. Altissimo, K. Nugent, and A. Peele, “Quantitative phase measurement in coherent diffraction imaging,” Opt. Express 16, 3342 (2008). [CrossRef] [PubMed]

]. Standard methods of filtered back projection [33

33. A. C. Kak and M. Slaney, Principles of Computerized Tomographic Imaging (Society for Industrial Mathematics, 1988).

] can then be used to obtain the 3D distribution of either quantity.

We now provide simulation and experimental results showing that 3D reconstructions can be successfully obtained using this approach, and quantify the increase in convergence speed.

3. Simulations

In order to explore the reconstruction methods, the geometry and parameters from a typical FCDI x-ray experiment were used [see Fig. 1 (left)]. A single element 3D object was analytically created for simulation purposes. The object represents a glass capillary used as a tomography sample mount in x-ray experiments. The large phase contrast between glass and carbon (an order of magnitude in δ at the energies explored in this paper) is also desirable. The simulated capillary is modelled on an FCDI reconstruction of the projection of an actual fractured capillary [Fig. 2(a)] obtained using the setup and method described in [26

26. J. Clark, C. Putkunz, M. Pfeifer, A. Peele, G. Williams, B. Chen, K. Nugent, C. Hall, W. Fullagar, S. Kim, and I. McNulty, “Use of a complex constraint in coherent diffractive imaging,” Opt. Express 18, 1981–1993 (2010). [CrossRef] [PubMed]

]. The corresponding 3D analytical model and its projection are identical to the eye in this reconstruction, shown in Fig. 2(b) and 2(c). The capillary has a diameter of 3μm and a wall width of 400nm.

The complex refractive index for the simulated object was taken from [34

34. B. L. Henke, E. M. Gullikson, and J. C. Davis, “X-ray interactions: Photoabsorption, scattering, transmission, and reflection at e = 50–30,000 ev, z = 1–92,” Atomic Data and Nuclear Data Tables 54, 181–342 (1993). [CrossRef]

] at an x-ray energy of 2.54keV, assuming a composition of Schott 8092 glass [35

35. J. U. Dumbaugh, “Method for making glass articles with defect-free surfaces,” US Patent No.4102,664(1978).

] with a density of 3.01g/cm 3.

The 2D phase and amplitude of the sample exit wavefield for a given projection, ψ e, θ(r s), in the projection approximation [27

27. D. Paganin, Coherent X-Ray Optics (Oxford University Press, 2006). [CrossRef]

] were obtained using:

ψe,θ(ρs,zS)=Tθ(ρs)ψ0(ρs,zS),
(4)

where r s = (ρs,zS) are the coordinates in the exit plane of the sample. Tθ(ρs) describes the complex transmission function of the object for the current projection angle as a function of the 3D complex refractive index n(r s) = 1 - δ(r s) + (r s). Using appropriate coordinate transformations:

Fig. 1. Experimental Parameters.
Fig. 2. (a) Amplitude of the transmission function of an actual glass capillary reconstructed from an FCDI tomography data set. This dataset was used to define the parameters for the simulated data set used in this study. (b) Projection through the 3D reconstruction of the simulated capillary used throughout this study, showing the amplitude of the transmission function. The colour scale in both (a) and (b) represents x-ray transmission from 50% (blue) to 100% (white). (c) 3D reconstruction of the δ component of the refractive index, sectioned to display the central region. (d) and (e) Slices through the reconstructed glass capillary for the δ and β components of the refractive index. The red box indicates the regions from which the components were averaged.
Tθ(ρs)=exp[k2izp[1n2(ρs,zp)]dzp].
(5)

Various “multi-slice” methods [36–38

36. J. M. Cowley and A. F. Moddie, “The scattering of electrons by atoms and crystals. i. a new theoretical approach,” Acta Crystallogr. 10, 609–619 (1957). [CrossRef]

] for calculating the exit surface wave of an illuminated object were explored. These build on the projection method in a slice by slice fashion. However, for the geometry in these, and other typical FCDI experiments, there was no significant difference between the “multi-slice” approximations and the exit surface wave obtained under the projection approximation.

Exit surface waves for different projections of the sample were calculated at 1° increments between ±π2 . The resulting exit surface waves were then propagated to the far field using the paraxial Fresnel free space propagator in Eq. (2). All phase information was then discarded in obtaining the squared amplitude of the diffracted wave, Iθ(ρd) = ∣ψ̂θ(ρd)∣2, as would be the case in a typical CDI experiment.

Reconstructions were performed on the complete dataset using the method described in Section 2. Figure 3(a) shows the advantage of bootstrapping using the reconstruction of the nth projection as a starting guess for the n + 1th projection. The dashed lines in Fig. 3 show the number of iterations required for the χ 2 error metric to converge (F ≤ 10−4) between successive iterates. The solid lines indicate the number of iterations required for each projection when using the bootstrap method. Figure 3(a) shows up to a 10 × speed increase for the total 3D reconstruction time, even in the presence of experimental noise.

Fig. 3. (a) The number of iterations required to reach a self-consistent solution at the 1.0 × 10−4 level in simulated data. (b) Iterations required to reach a self-consistent solution at the 1.0 × 10−3 level during reconstructions of the insect wing.

Slices through the δ and β components of the reconstructed object obtained using the bootstrap method are shown in Figs. 2(d) and 2(e) respectively. The recovered values, tabulated in Fig. 4, show the bootstrap and standard methods to be quantitatively very similar. The recovered values are also in good agreement with the actual values.

Similar results in speed up and quantitative recovery of the refractive index have been obtained for other objects, including those that are non-cylindrically symmetric and are composed of multiple materials.

4. Optical Experiments

Experimental FCDI tomography data was collected using coherent monochromatic focused (NA = 19.6) optical laser light using the experimental parameters in Fig. 1 (right). The focused beam illuminated the wing tip of an insect [see Fig. 5(c)] with a field of view of approximately 1 mm 2.25 frames of diffraction data, each 1 second long were taken for each projection between ±π2 , at 12° increments. This provided a high enough signal to noise for scattered photons to be measured at the edge of the detector array [see Fig. 5(a)]. Reconstructions were performed using the method described in Section 2.

A single projection through the 3D reconstruction is shown in Fig. 5(b), with the rendered 3D reconstruction in Fig. 5(d). An obvious likeness can be seen with the corresponding optical microscope image shown in Fig. 5(c). The differences in the appearance of the wing tip between Figs. 5(b) and 5(c) are due to artifacts in the FCDI reconstruction. A contributing cause of these artifacts is specular reflections from the surface of the wing.

Notwithstanding these issues, the bootstrap process is shown in Fig. 3(b) to provide a computational advantage. An improvement by a factor of ~ 2 is observed compared to the standard method. At the same time the reconstruction quality was not compromised.

Fig. 4. Average reconstructed values for the x-ray simulation in the regions indicated in Fig. 2(d) and 2(e). Errors are calculated from the standard deviation of the region of interest.
Fig. 5. (Media 1) (a) 25 combined frames of optical coherent diffraction data corresponding to ∣ψ̂∣2. Data has been logarithmically scaled to better depict both high angle scatter and holographic region. (b) Reconstruction of a single projection, showing the amplitude of the transmission function, ∣T∣. (c) Optical microscopy image of the damaged wing tip. (d) 3D rendering of reconstructed insect wing. In this qualitative view colours of features in the rendering were based on the segmentation of well-defined components in the histogram of densities.

5. Computational Bootstrap Benefits

The relative advantages of 3D CDI and the bootstrap methods can be quantified by considering the amount of memory, and the order of the number of operations required to obtain a reconstruction. We also consider the curved beam analogue of 3D CDI, namely 3D FCDI. To date 3D FCDI has not been demonstrated; here we consider what the load may be should the technique be elucidated.

If N = 2048 is the linear dimension of the detector array, then the 3D complex diffraction volumes for 3D CDI and 3D FCDI would occupy 296 GB of RAM. In our case the bootstrap FCDI code requires less than 1 GB, corresponding to the measured diffraction data and illumination for a single angular projection.

Fig. 6. The nominal number of computational operations used in various 3D reconstruction techniques.

In a typical FCDI tomography reconstruction N = 2048 and M = 500. While the optimal number of angular projections to reconstruct an object spanning N pixels using filtered back projection is π2N [40

40. P. Cloetens, “Contribution to phase contrast imaging, reconstruction and tomography with hard synchrotron radiation,” Ph.D. thesis, Faculteit Toegepaste Wetenschappen, Vrije Universiteit Brussel (1999).

], we assume P = 180 as a more experimentally attainable number. Using these figures, and assuming an S = 5 × speed increase for bootstrapped projections leads to the total number of operations described in Fig. 6.

6. Conclusion

Using simulations and experimental data we demonstrated that the bootstrap method can provide significant computational advantages in FCDI tomography, which can be extended to the plane wave geometry of CDI. These advantages may be a speed increase of the order of 10 ×. This figure can be even higher, for instance when providing multiple seeds to the set of reconstructions, or in the case of small angular steps or high object symmetry. The memory and storage overhead of the bootstrap method is also far less than the direct 3D methods, allowing it to run on a single processor desktop computer while still obtaining 3D reconstructions for large arrays. A further advantage of FCDI tomography is the ability to image objects which extend beyond the illumination in the vertical direction. In 3D CDI this is complicated due to the requirement for finite object support. Objects that are large laterally can also be imaged using the ptychography approach [41

41. D. Vine, G. Williams, B. Abbey, M. Pfeifer, J. Clark, M. de Jonge, I. McNulty, A. Peele, and K. Nugent, “Ptychographic fresnel coherent diffractive imaging,” Phys. Rev. A 80, 063823 (2009). [CrossRef]

]. This will further increase the size of the data set involved and increase computation times. The combination of bootstrapped tomography with ptychography will greatly reduce the total computational time required to obtain high quality 3D reconstructions.

Acknowledgments

The authors acknowledge support from the Australian Research Council Centre of Excellence and Fellowship Programs. This project was supported by the Victorian Partnership for Advanced Computing HPC Facility and Support Services. Use of the Advanced Photon Source is supported by the U.S. Department of Energy, Office of Science, and Office of Basic Energy Sciences, under Contract No. DE-AC02-06CH11357.

References and links

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H. Chapman, A. Barty, S. Marchesini, A. Noy, S. Hau-Riege, C. Cui, M. Howells, R. Rosen, H. He, J. Spence, U. Weierstall, T. Beetz, C. Jacobsen, and D. Shapiro, “High-resolution ab initio three-dimensional x-ray diffraction microscopy,” J. Opt. Soc. Am. A. 23, 1179–1200 (2006). [CrossRef]

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J. Miao, K. Hodgson, T. Ishikawa, C. Larabell, M. LeGros, and Y. Nishino, “Imaging whole escherichia coli bacteria by using single-particle x-ray diffraction,” Proc. Nat. Acad. Sci. USA 100, 110–112 (2003). [CrossRef] [PubMed]

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E. Lima, L. Wiegart, P. Pernot, M. Howells, J. Timmins, F. Zontone, and A. Madsen, “Cryogenic x-ray diffraction microscopy for biological samples,” Phys. Rev. Lett. 103, - (2009). [CrossRef]

13.

X. Huang, J. Nelson, J. Kirz, E. Lima, S. Marchesini, H. Miao, A. Neiman, D. Shapiro, J. Steinbrener, A. Stewart, J. Turner, and C. Jacobsen, “Soft x-ray diffraction microscopy of a frozen hydrated yeast cell,” Phys. Rev. Lett. 103, 198101 (2009). [CrossRef]

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16.

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18.

P. Thibault, M. Dierolf, A. Menzel, O. Bunk, C. David, and F. Pfeiffer, “High-resolution scanning x-ray diffraction microscopy,” Science 321, 379–382 (2008). [CrossRef] [PubMed]

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R. Bates, “Uniqueness of solutions to two-dimensional fourier phase problems for localized and positive images,” Comput. Vision Graph. 25, 205–217 (1984). [CrossRef]

20.

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21.

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H. Quiney, A. Peele, Z. Cai, D. Paterson, and K. Nugent, “Diffractive imaging of highly focused x-ray fields,” Nat. Phys. 2, 101–104 (2006). [CrossRef]

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B. Abbey, K. Nugent, G. Williams, J. Clark, A. Peele, M. Pfeifer, M. De Jonge, and I. McNulty, “Keyhole coherent diffractive imaging,” Nat. Phys. 4, 394–398 (2008). [CrossRef]

25.

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I. Johnson, K. Jefimovs, O. Bunk, C. David, M. Dierolf, J. Gray, D. Renker, and F. Pfeiffer, “Coherent diffractive imaging using phase front modifications,” Phys. Rev. Lett. 100, 155503 (2008). [CrossRef] [PubMed]

30.

R. W. Gerchberg and W. O. Saxton, “A pratical algorithm for the determination of phase from image and diffraction plane pictures,” Optik (Stuttgart) 35, 237–246 (1972).

31.

J. R. Fienup, “Reconstructions of an object from the modulus of its fourier transform,” Opt. Lett. 3, 27–29 (1978). [CrossRef] [PubMed]

32.

J. Clark, G. Williams, H. Quiney, L. Whitehead, M. de Jonge, E. Hanssen, M. Altissimo, K. Nugent, and A. Peele, “Quantitative phase measurement in coherent diffraction imaging,” Opt. Express 16, 3342 (2008). [CrossRef] [PubMed]

33.

A. C. Kak and M. Slaney, Principles of Computerized Tomographic Imaging (Society for Industrial Mathematics, 1988).

34.

B. L. Henke, E. M. Gullikson, and J. C. Davis, “X-ray interactions: Photoabsorption, scattering, transmission, and reflection at e = 50–30,000 ev, z = 1–92,” Atomic Data and Nuclear Data Tables 54, 181–342 (1993). [CrossRef]

35.

J. U. Dumbaugh, “Method for making glass articles with defect-free surfaces,” US Patent No.4102,664(1978).

36.

J. M. Cowley and A. F. Moddie, “The scattering of electrons by atoms and crystals. i. a new theoretical approach,” Acta Crystallogr. 10, 609–619 (1957). [CrossRef]

37.

A. R. Hare and G. R. Morrison, “Near-field soft x-ray diffraction modelled by the multislice method,” J. Mod. Opt. 41,31–48 (1994). [CrossRef]

38.

P. Thibault, V. Elser, C. Jacobsen, D. Shapiro, and D. Sayre, “Reconstruction of a yeast cell from x-ray diffraction data,” Acta Crystallogr. A 62, 248–261 (2006). [CrossRef] [PubMed]

39.

G. Williams, M. Pfeifer, I. Vartanyants, and I. Robinson, “Effectiveness of iterative algorithms in recovering phase in the presence of noise,” Acta Crystallogr. A 63, 36–42 (2007). [CrossRef]

40.

P. Cloetens, “Contribution to phase contrast imaging, reconstruction and tomography with hard synchrotron radiation,” Ph.D. thesis, Faculteit Toegepaste Wetenschappen, Vrije Universiteit Brussel (1999).

41.

D. Vine, G. Williams, B. Abbey, M. Pfeifer, J. Clark, M. de Jonge, I. McNulty, A. Peele, and K. Nugent, “Ptychographic fresnel coherent diffractive imaging,” Phys. Rev. A 80, 063823 (2009). [CrossRef]

OCIS Codes
(340.7440) X-ray optics : X-ray imaging
(340.7460) X-ray optics : X-ray microscopy

ToC Category:
X-ray Optics

History
Original Manuscript: February 17, 2010
Revised Manuscript: April 8, 2010
Manuscript Accepted: May 4, 2010
Published: May 19, 2010

Virtual Issues
Vol. 5, Iss. 10 Virtual Journal for Biomedical Optics

Citation
C. T. Putkunz, M. A. Pfeifer, A. G. Peele, G. J. Williams, H. M. Quiney, B. Abbey, K. A. Nugent, and I. McNulty, "Fresnel coherent diffraction tomography," Opt. Express 18, 11746-11753 (2010)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=oe-18-11-11746


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References

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