THREE DIMENSIONAL IMAGING IN SCANNING SOFT X-RAY MICROSCOPY

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THREE DIMENSIONAL IMAGING IN SCANNING SOFT X-RAY MICROSCOPY

L. Cheng, A. Michette

To cite this version:

L. Cheng, A. Michette. THREE DIMENSIONAL IMAGING IN SCANNING SOFT X- RAY MICROSCOPY. Journal de Physique Colloques, 1984, 45 (C2), pp.C2-97-C2-100.

�10.1051/jphyscol:1984224�. �jpa-00223888�

JOURNAL DE PHYSIQUE

Colloque C2, supplément au n°2, Tome 45, février 1984 page C2-97

THREE DIMENSIONAL IMAGING IN SCANNING SOFT X-RAY MICROSCOPY L.M. Cheng and A.G. Michette

Physios Department, Queen Elizabeth College, University of London, Campden Hill Road, London W8 7 AH, U.K.

Résumé - En reconstruction d'image à trois dimensions, on a besoin d'un ensemble complet de projections d'images bidimensionnelles pour obtenir une reconstruction non-ambiguë de l'objet. En pratique, particulièrement pour le microscope par rayons-X à balayage, l'angle d'inclinaison de l'objet est géométriquement limité et la reconstruction à partir d'un ensemble incomplet de projections sera spatialement déformée. Pour améliorer ceci on Utilise l'information a priori Pour un microscope par rayons-X à balayage, l'illumination avec un faisceau en éventail et un réseau linéaire de détecteurs sera adéquate pour donner un ensemble de projections 2-D.

Une autre solution qui peut être moins exigeante en ce qui concerne le balayage et l'inclinaison est d'utiliser l'illumination à faisceau conique et un réseau de dé- tecteurs 2-D. Les différences en reconstruction d'image utilisant ces deux systèmes peuvent être étudiées en utilisant un analogue optique en similitude géométrique.

Abstract - In 3-D image reconstruction, a complete set of 2-D image projections are required to give a unique and unambiguous object reconstruction. In practice, part- icularly for a scanning X-ray microscope, the tilting angle of the object is geomet- rically restricted and the reconstruction from an incomplete projection set will be spatially distorted; one way to improve this is to use a priori information. For a scanning X-ray microscope, a fan beam illumination and a linear array detector will be adequate to provide a set of 2-D projections. An alternative, which may place less stringent requirements on the scanning and tilting mechanism, is to use cone beam illumination and a 2-D array detector. The differences in image reconstruction using these two systems can be investigated using a geometrically scaled optical analogue.

Introduction

The algorithms used in reconstructing 3-D images from a set of projections have been well established in the field of computerised tomography CCT) [1]. The same ideas can be applied to X-ray microscopy. However, the differences in the instrumental set-up of these two systems may generate extra difficulties in reconstructing 3-D images from projections in X-ray microscopy. In CT, the most popular reconstruction algorithm, the filtered backprojection method, requires a parallel source and a com- plete set of projections (±90°). However, since X-ray sources generate divergent beams, extra pre-propessing of data, such as rebinning algorithms, and/or complicat- ed (e.g. iterative) techniques, are necessary. Moreover, if the instrument.is too geo- metrically restricted to give a complete set of tilting angles, the conventional re- construction methods will either break down or give ambiguous solutions. In order to obtain an optimum solution from an incomplete set of projection data, a priori

information and the minimum norm technique may be used [2].

In this paper, we discuss (i) (briefly) the various reconstruction techniques using projection data, (ii) the minimum norm approach for reconstructing an image from an incomplete set of projections and (iii) the possibility of building an optical ana- logue (which can operate in a more stable and controllable environment) of the X-ray microscope, for justifying the 3-D image reconstruction techniques proposed.

Article published online by EDP Sciences and available at http://dx.doi.org/10.1051/jphyscol:1984224

C2-98 JOURNAL DE PHYSIQUE

Image reconstruction from projections

To simplify the mathematical illustration of the reconstruction method, we consider the theory using a 2-D approach. The methods can be used to reconstruct the 3-D object either 1) by segmenting the object into 2-D parallel slices, or 2) by extend- ing the methods into 3-D space.

Given an object f(x,y) which is tilted at an angle 8, the intensity detected along a line with parallelillumination is given by

T~(x) = jf(x,y) dy

where Ie(x) is the projection function and the coordinate system is defined in fig- ure 1 which shows the formation of projections from a cross-section (or slice) of a

3-D object. , , . . . , * . , , , ,

n

DATA POINl

A) A test phantom for the computer simulation

B) The prior knowledge used for limited angle reconstruction

C) A typical projection at tilting angle of 30°using parallel illumination Fig. 1

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To obtain the solution to the object function f(x,y) from a complete set of project- ion intensities Ie(x) methods have been developed by various authors (full details of these algorithms and the references are given in [I]). These methods fall into 3 basic groups: 1) direct analytical, 2) Fourier analytical and 3) iterative.

The direct analytical methods are the simplest approach to give an approximate sol- ution. They consist of backprojection, deconvolution and filtered backprojection.

Backprojection is based on superimposing the 2-D backprojected image of projection lines at various angles on top of each other. The result gives a convoluted image due to the impulse response of the backprojecting process (= I/r where r is the dis- tance from the object centre). To obtain an unconvoluted reconstruction, the result needs to be deconvolved using the impulse response function. Alternatively, the pro- jection can be deconvolved or filtered before the backprojection process takes place in order to compensate the impulse response effect (i.e. filtered backprojection).

The Fourier analytical method is based on the central projection theorem of the Fourier transform. The Fourier transform of the projection obtained at angle 8 is equivalent to the line along 8 of the Fourier transform of the 2-D object. The dif- ficulty of using this method is the interpolation of a polar sample to a cartesian equivalency in the Fourier space such that the reverse transform can be performed to obtain the reconstructed image.

The iterative methods are based on making an initial guess and then improving the solution by modifying the guess iteratively until the projections obtained from the guessed solution match with those of the experimental projections. The developed iterative methods are arithematic reconstruction techniques (ART, additive andmulti-

plicative) and simultaneous iterative reconstruction techniques(S1~T). The disad- vantages are slow operation and large computer overheads.

So far, we have restricted ourselves for simplicity to considering projections form- ed by parallel illumination. For X-ray microscopy, it is more realistic to consider a divergent beam, i.e. a fan or cone beam. The data obtained require further re- sampling from divergent illumination into parallel beam equivalency using rebinning techniques before they can be operated on by the methods designed for parallel ill- umination.

Image reconstruction from limited projections

In high resolution X-ray microscopy using zone plates, the distance between the ob- jective zone plate and the focus is restricted to the order of mm or less. Thus, in practice, it is very difficult to obtain a complete set of projections covering all tilting angles. This results in ambiguous solutions if conventional techniques are used. To improve the solutions, the approach suggested by Byrne and Fitzgerald [ 2 ] may be used where the signal restoration problem is formulated in a weighted Hilbert

space. Instead of restoring the signal by extrapolating the unknown coefficients in the Fourier space, as in [ 2 ] , we consider that in the frequency space there exists an approximate convolution between a set of unknown but optimum coefficients and the Hilbert space weighting function. If we specifically choose the weighting function to be some pre-known function, for example the expected shape of the object, we can retrieve the unknown coefficients by dividing the degraded object function by thede- graded a priori information. From these coefficients, we can calculate the restored image, optimum in the sense that it is the unique minimum norm estimate consistent with the initial data. Figure 2 shows the reconstruction of an object from limited projections using a priori information.

A) Test phantom

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B ) Reconstructed object from full set of projections using ART

+ 0

C) Reconstructed object from limited projections between - 60 using ART D) Improved reconstructed object using prior knowledge

Fig. 2

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A practical design of an optical analogue of a scanning X-ray microscope

The system to be used for the 3-0 reconstruction of X-ray microscope projections may be designed and tested using, for example, computer or optical simulation. Such tests are cheaper and easier to perform than using an actual X-ray microscope set-up.

We choose the use of optical simulation because it is closer to realistic operation of an X-ray microscope system, and we also have experience in designing optical ana- logues to the conventional and scanning transmission electron microscopes. This provides a simple, controllable, flexible and economical system for investigating the available detection and reconstruction techniques. The optical analogue system is shown in figure 3.

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SPATIAL

FILTER OBJECT (SCAN AND TILT) I

ZONE PLATE 1 ZONE PLATE 2 DETECTOR (VIDEO CAMERA)

m

1 I

ELECTRONICS COMPUTER

Fig. 3

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FRAME I VIDEO RECORDER

STORE (OPTIONAL)

The source used is a He-Ne laser with output wavelength of 632.8 nm or, more realis- tically, an intense broad band source. The condenser and objectivelenses are zone plates which match those to be used in the X-ray microscope as closely as possible.

The object is scanned using a stage driven by two orthogonal stepping motors operat- ing at 200 Hz. The object is some well-defined test shape. The detector is a high resolution TV-video camera; the video signal can be optionally recorded and stored for future processing, or can be fed directly into a Gresham-Lion frame store system which digitises the signal and performs some pre-processing, for example signal aver- aging, filtering, or frame averaging. The Gresham-Lion frame store system consists of a fast analogue to digital converter, a central processor, 8-bit 512x1024 picture memory and 10-bit full colour look up table. The digitised signal can be transmitt- ed directly into the data storage and acquisition computer (Digital VAX 11/780) for more sophisticated processing.

Conclusions

Algorithms for 3-D reconstruction from limited projections are available and, with some development, are suitable for X-ray microscope images. The most convenient way of testing these algorithms is to use an optical analogue of the X-ray microscope.

Acknowledgements

We are grateful to the Science and Engineering Research Council (SERC) for financial support.

References

[ I ] HERMAN G.T. 'Image reconstruction from projections

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[2] BYRNE, C.I. and FITZGERALD R.M. 'Reconstruction from partial inFormation with application to tomography1, SIAM, Appl. Math. 42 No. 4 Aug. 1982 p.933-940.