Near, far, wherever you are: simulations on the dose efficiency of holographic and ptychographic coherent imaging

Abstract

Different studies in X-ray microscopy have arrived at conflicting conclusions about the dose efficiency of imaging modes involving the recording of intensity distributions in the near (Fresnel regime) or far (Fraunhofer regime) field downstream of a specimen. A numerical study is presented on the dose efficiency of near-field holography, near-field ptychography and far-field ptychography, where ptychography involves multiple overlapping finite-sized illumination positions. Unlike what has been reported for coherent diffraction imaging, which involves recording a single far-field diffraction pattern, it is found that all three methods offer similar image quality when using the same fluence on the specimen, with far-field ptychography offering slightly better spatial resolution and a lower mean error. These results support the concept that (if the experiment and image reconstruction are done properly) the sample can be near or far; wherever you are, photon fluence on the specimen sets one limit to spatial resolution.

Fast digital lossy compression for X-ray ptychographic data

“…Phantom cell object (a) and limited-area coherent illumination spot [(b), the 'probe function'] used for our simulations. The 325 Â 325 pixel phantom cell is the same pure-phase object used in previous studies of the effect of changing photon fluence in different X-ray microscopy methods (Hagemann & Salditt, 2017;Du et al, 2020). The probe function's intensity is shown at the same scale here, but it is in fact a 72 Â 72 pixel array which is scanned across the phantom, with the boundaries of the probe array indicated by a green box.…”

“…in this case. Prior studies (Du et al, 2020) have shown that one can then estimate the required fluence from…”

“…While many researchers use spiral probe scans to avoid grid artifacts (Thibault et al, 2009;Dierolf et al, 2010b), we have modeled the use of rectangular scans which are better suited to constant-velocity continuous scanning (Pelz et al, 2014;Deng et al, 2015;Huang et al, 2015), and which do not display artifacts if sufficient probe overlap is used (Bunk et al, 2008;Huang et al, 2014). The shift between probe positions was set to 5 pixels to provide a very high degree of overlap, which is of particular importance at low fluence levels (Du et al, 2020). (Even so, a slight grid artifact is present which affects some FRC values as noted in Fig.…”

“…The images in successive columns are from a simulated dataset with no encoding (left), and then with loss encoding schemes (a), (b), and (c) in the subsequent columns. These images were obtained using a least-squares cost function, rather than a Poisson noise cost function, which leads to a smoothed appearance at low fluences (Du et al, 2020). Use of the lossy encoding scheme (a) has almost no effect on reconstructed image quality, while the increasing degree of loss provided in schemes (b) and especially (c) lead to lower quality reconstructed images at very low fluence.…”

“…At low spatial frequency u, two independent reconstructed images with low fluence will have high correlation due to the same rough outline of the feature existing even for poor-resolution images. Since one needs more fluence to see finer features in coherent X-ray imaging (Huang et al, 2009;Schropp & Schroer, 2010;Godard et al, 2012;Jahn et al, 2017;Hagemann & Salditt, 2017;Du et al, 2020), it is common to use the crossing between the FRC and a 1/2 bit threshold criterion (van Heel & Schatz, 2005) as a measure of the achieved spatial resolution in an image. For the 1/2 bit threshold, we calculated the FRC between two full images instead of two half images as described by van Heel & Schatz, (2005).…”