Optical diffractive tomographic microscopy is a new wide-field, non-invasive and label-free three-dimensional (3D) imaging technology for cells and tissues, which has great application prospects in cell metabolism, pathology and tumor diagnosis. However, with the continuous development of modern biological research, the field-of-view (FOV) of traditional optical diffractive tomography (ODT) cannot meet the needs of observation any more. The invention of large field-of-view ODT technology, while maintaining subcellular resolution, is in an increasingly urgent need.
At present, various quantitative phase imaging technologies require higher spatial-bandwidth product. For example, the sampling rate of interference streaks acquisition in off-axis holographic imaging is more than three times that of intensity imaging. In the condition of a certain number of camera pixels, only a small FOV can be acquired. In order to conduct large-FOV quantitative phase imaging, the number of pixels in the single image is doubled, and the data flux of images is too large. It leads to the facts that the image storage becomes more difficult, the complexity of recovery algorithm is aggravated, and the time of settlement increases.
The traditional method to realize large FOV is to scan different areas and then splice the images. However, the method is not suitable for living cells since they constantly move, which limits the further application of the traditional ODT method in biology. To solve the problem, we propose a new ODT technology which can realize the large FOV.
Based on the Mach-Zehnder transmission holographic imaging system, we make some unique designs for large-FOV imaging requirements. The main innovations are described here.
Firstly, we design a non-destructive pupil holographic beam binding scheme. We use the D-shaped mirror instead of beam splitters for beam combining. It can achieve zero loss of intensity and unlimited size. Secondly, we achieve large-FOV oblique plane illumination under the large numerical aperture (NA). Finally, we improve the image acquisition system. We choose a 21 megapixels camera and the faster CoaXPress-12 card as the data acquisition card, and achieve the 50 Gbit/s data flux. The optical elements and galvanometer of the system are re-selected to ensure that there is no aperture limitation.
In addition, we rewrite the data processing program, considering the large amount of data in the large-FOV ODT system. We reconstruct the software of images acquisition to realize the high-speed image acquisition and storage. Then, we edit the new multithread ODT recovery algorithm based on C++ for 64-bit system, which can automatically recover all the collected data synchronously. Using the above system and algorithm, we image 5 μm polystyrene microspheres to verify the feasibility of the system. Then, Hela cells are imaged, which verifies that the method has long-term 3D observation ability for dense tissue cells and living cells.
In this paper, a large-FOV optical diffraction tomography technique is proposed. The large-FOV ODT uses all the FOV of the objective lens to reach the limit of the imaging range. At the same time, it has both high resolution and long-term 3D imaging capability for living cells. Compared with the traditional ODT system, the imaging range of the proposed system is larger [Figs. 3(a) and 5(a)]; more photons scattered by complex samples can be obtained, so that the signal-to-noise ratio (SNR) is better [Figs. 3(b) and 3(c)]. Moreover, the ringing and artifacts effects of the edge are smaller [Figs. 3(b), 3(c), 5(b), and 5(c)]. The interaction between cells, as well as more cells in different states, can be observed simultaneously in a FOV (Figs. 5 and 6).
The results show that the large-FOV optical diffraction tomography technology has both subcellular resolution and long-term 3D observation ability of label-free living cells. Compared with the traditional system, the large-FOV ODT system has smaller edge effects and obtains more information of cells, so it is beneficial to observing the interaction between cells, and is helpful to realizing the long-term 3D observation of huge living cells such as oocytes. It will have more biological applications.
