The Best of Both Worlds: 3D X-ray Microscopy with Ultra-high Resolution and a Large Field of View

W. Lia, J. Gelbb, Y. Yanga, Y. Guana, W. Wua, J. Chena, and Y. Tiana,*

aNational Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei, Anhui, 230029, P. R. China

bXradia, Inc., 5052 Commercial Cir., Concord, CA, 94520, USA *E-mail: ychtian@ustc.edu.cn

Abstract. 3D visualizations of complex structures within various samples have been achieved with high spatial resolution by X-ray computed nanotomography (nano-CT). While high spatial resolution generally comes at the expense of field of view (FOV). Here we proposed an approach that stitched several 3D volumes together into a single large volume to significantly increase the size of the FOV while preserving resolution. Combining this with nano-CT, 18-m FOV with sub-60-nm resolution has been achieved for non-destructive 3D visualization of clustered yeasts that were too large for a single scan. It shows high promise for imaging other large samples in the future.

Keywords: Nanotomography, synchrotron radiation, large field of view, yeasts PACS: 68.37.Yz

INTRODUCTION

X-ray computed tomography (CT) is a powerful tool that non-destructively generates three-dimensional images of an object’s interior from a series of two-dimensional X-ray images taken around a single axis of rotation. During the past two decades, the development of advanced x-ray optical devices, such as Fresnel zone plates, coupled with the high brilliance of synchrotron x-ray sources, has vastly increased the resolution of x-ray imaging. Resolution for 2D imaging down to 12-30 nm has been recently reported [1-4]; meanwhile 3D resolution to 30-60 nm and below is also now widely available [5-7]. This nano-CT technique has demonstrated many advantages in studying the 3D structures of complex samples at various length scales and has satisfied applications in a wide range of fields, such as material science [8-9], cellular biology [10-12], solid oxide fuel cells [13-14], and environmental science [15-17].

However, the high spatial resolution of nano-CT often comes at the expense of field of view (FOV) due, in part, to limitations in the available number of pixels in a typical CCD-based detector. A typical FOV available for the highest resolution, such as in the Xradia nanoXCT-S100 at National Synchrotron Radiation Laboratory (NSRL), Hefei, China, is about 10-15 m [6, 8-9]. These FOV limitations may not be optimal for some studies of larger samples, in which the volume of interest exceeds the volume available for a single scan.

While some hardware restrictions limit the achievable FOV when maintaining the same resolution, two different software methods exist to get larger 3D volumes. In the first method, several 2D images at each projection angle may be collected and stitched together into a single tilt series before reconstruction. This method, however, naturally increases the requirements on performance of the reconstruction computer and may be very sensitive to imaging artifacts due to image registration errors. Another alternative method is stitching each virtual slice of different 3D tomographic volumes together after the reconstructions of all radiographs, which does not impose any additional requirements on the present imaging and reconstruction system. Here, we demonstrated the capacity of the second method by stitching two 3D volumes of partial clustered yeast cells into a full 3D visualization of clustered yeast cells with about 18-m FOV instead of 10-m FOV from the original partial volumes.

The 10th International Conference on X-ray MicroscopyAIP Conf. Proc. 1365, 261-264 (2011); doi: 10.1063/1.3625354

© 2011 American Institute of Physics 978-0-7354-0925-5/$30.00

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MATERIALS AND METHODS

Sample Preparation and Nano-CT Experiments

Here, the wild type fission yeast Schizosaccharomyces pombe was used to demonstrate this method. The yeasts were cultured, fixed, and dehydrated by a process that has previously been proposed for hard X-ray imaging [18]. The samples were then spotted on a silicon nitride membrane of 100-nm thickness for mounting on the microscope sample holder. The tomography experiments were performed using the Xradia nanoXCT-S100 full-field transmission hard x-ray microscope (TXM), installed at beamline U7A of NSRL [6]. Operating at 8 keV and utilizing Zernike phase contrast, this TXM system has been demonstrated to effectively obtain 3D images of some low-absorbing specimens, such as stained yeasts with about sub-60-nm spatial resolution and 10-m FOV [18]. By aligning each yeast to the rotation center, two different CT scans were collected with the same exposure dose at angles ranging from –74º to +74º in 1º intervals using the Xradia TXMController software and reconstructed using the Xradia TXMReconstructor software [19].

Stitching Algorithm

Due to the experiments being performed using the same sample holder and rotation stage, there are only linear shifts between the series of tomographic volumes. If the same features are found in each of the two volumes, then the volumes can be aligned and stitched together into one large volume. A Matlab™ program was developed at NSRL to provide an automatic stitching process using this method, as shown in Fig. 1. Figures 1(a) and. 1(b) are two virtual slices of two different 3D volumes, which are each from one large test pattern. One array of dots, common to both volumes, was located and is indicated by the yellow rectangles. By using linear shifts only, the dots indicated by the red arrows may be matched to each other and the two volumes aligned. The best linear shifts can be estimated by a minimum square difference method. The rough coordinations of the same features in two reconstructed volumes were used as inputs for the Matlab™ program. Then two small cubic volumes with varying slight liner shifts were cropped and their square differences were calculated. So the minimum difference indicated the best linear shifts between the two volumes. The two volumes are subsequently stitched together using an overlapping smoothing function. The sizes of volume (a) and (b) are both about 10 × 10 × 10 m3 while the size of volume (c) is about 20 × 10 × 10 m3. It means that the stitching algorithm can easily achieve larger FOV than the normal results, which is useful for the study of some big samples.

FIGURE 1. A demonstration of the stitching algorithm. (a) and (b) are two virtual slices of two different reconstructed 3D volumes, in which the yellow rectangles indicate the common information (dots). (c) is the volume reconstructed

by stitching the two volumes of (a) and (b). The red arrows indicate which dots were used for alignment.

RESULTS AND DISCUSSION

Two yeast cells, located side-by-side in one sample, were slightly bigger than the size of a single reconstructed volume and, thus, could not be easily reconstructed into one volume by the standard procedure. The routine described above was then used, where two 3D volumes, shown in Figs. 2(a) and 2(b), were collected and the stitching algorithm applied, the results of which are shown in Fig. 2(c). The alignment features used are indicated by red arrows in Fig. 2(a) and Fig. 2(b). From the stitching volume in Fig. 2(c), two different sizes of yeast cells were

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clearly seen, and the reconstructed volume increased to 12.4 × 17.4 × 16.9 m3, double the standard volume for sub-60-nm resolution.

FIGURE 2. Three stacks of yeast cells. Upper image of each stack is a single virtual slice of the 3D volume while lower image of each stack is the 3D rendering. The volume of (c) is created by stitching the two volumes in (a) and (b).

The red arrows indicate the same features in both volumes which were used for alignment.

FIGURE 3. Visualization of the clustered yeast cells. (a) One radiograph of the clustered yeast cells. (b) 3D visualization of the reconstructed clustered yeast cells. The red arrows indicate the cell wall and the yellow arrows indicate the vacuoles that were

imaged by the nano-CT in both yeast A and yeast B. The green arrows indicate the possible location of the invisible nucleus.

Figure 3(a) shows a single radiograph of the region of interest with the two clustered yeast cells centered and Fig. 3(b) shows the segmented 3D volume. The measured length and width are about 7.38 m and 3.65 m, respectively, for yeast A, and about 5.97 m and 2.93 m, respectively, for yeast B. The thick cell walls indicated by the red arrows were clearly seen, with measured thicknesses ranging between 300-500 nm. In addition, several small, sphere-like structures are observed inside the cells, which, by comparison to the results from the electron microscope [20, 21], can be verified as the vacuoles. Due to the low contrast of the nucleus, it can not be imaged by our hard x-ray microscopy; however, the distribution of the vacuoles suggests a possible location of the nucleus, which is indicated by the green arrows. Table 1 lists the measured volumes and the volume fractions of the different sub-cellular components.

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TABLE 1. The Measured Volumes and Volume Fractions of Different Cellular Components Yeasts Cell wall Vacuoles Others No. Volumes Vol. fraction Volumes Vol. fraction Volumes Vol. fraction Yeast A m3 35.2 % m3 3.6 % m3 61.2 % Yeast B m3 42.9 % m3 2.6 % m3 54.5 %

CONCLUSION

Here, a stitching method has been proposed to reconstruct volumes larger than the normal FOV of a TXM system by correlation of different 3D volumes. This technique has been applied to clustered yeast cells that were thus reconstructed in their entirety with sub-60-nm resolution. The results suggest a novel, useful technique for studying samples that may normally be limited by the standard FOV, which may extend the potential applications of commercially available nano-CT instruments in various fields.

ACKNOWLEDGMENTS

The authors are grateful for the financial support from the 985 project of the State Ministry of Education, the National Science Foundation of China (Grant No. 10734070), and the Knowledge Innovation Program of the Chinese Academy of Sciences (KJCX2-YW-N43).

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