X-ray tomography of extended objects: a comparison of data acquisition approaches

The penetration power of x-rays allows one to image large objects. For example, centimeter-sized specimens can be imaged with micron-level resolution using synchrotron sources. In this case, however, the limited beam diameter and detector size preclude the acquisition of the full sample in a single take, necessitating strategies for combining data from multiple regions. Object stitching involves the combination of local tomography data from overlapping regions, while projection stitching involves the collection of projections at multiple offset positions from the rotation axis followed by data merging and reconstruction. We compare these two approaches in terms of radiation dose applied to the specimen, and reconstructed image quality. Object stitching involves an easier data alignment problem, and immediate viewing of subregions before the entire dataset has been acquired. Projection stitching is more dose-efficient, and avoids certain artifacts of local tomography; however, it also involves a more difficult data assembly and alignment procedure, in that it is more sensitive to accumulative registration error

Digital autofocusing of a coded-aperture Laue diffraction microscope

To provide optimal depth resolution with a coded-aperture Laue diffraction microscope, an accurate position of the coded-aperture and its scanning geometry need to be known. However, finding the geometry by trial and error is a time-consuming and often challenging process because of the large number of parameters involved. In this paper, we propose an optimization approach to automate the focusing process after data is collected. We demonstrate the robustness and efficiency of the proposed approach with experimental data taken at a synchrotron facility

Depth-resolved Laue microdiffraction with coded-apertures

We introduce a rapid data acquisition and reconstruction method to image the crystalline structure of materials and associated strain and orientations at micrometer resolution using Laue diffraction. Our method relies on scanning a coded-aperture across the diffracted x-ray beams from a broadband illumination, and a reconstruction algorithm to resolve Laue microdiffraction patterns as a function of depth along the incident illumination path. This method provides a rapid access to full diffraction information at sub-micrometer volume elements in bulk materials. Here we present the theory as well as the experimental validation of this imaging approach

Three dimensions, two microscopes, one code: automatic differentiation for x-ray nanotomography beyond the depth of focus limit

Conventional tomographic reconstruction algorithms assume that one has obtained pure projection images, involving no within-specimen diffraction effects nor multiple scattering. Advances in x-ray nanotomography are leading towards the violation of these assumptions, by combining the high penetration power of x-rays which enables thick specimens to be imaged, with improved spatial resolution which decreases the depth of focus of the imaging system. We describe a reconstruction method where multiple scattering and diffraction effects in thick samples are modeled by multislice propagation, and the 3D object function is retrieved through iterative optimization. We show that the same proposed method works for both full-field microscopy, and for coherent scanning techniques like ptychography. Our implementation utilizes the optimization toolbox and the automatic differentiation capability of the open-source deep learning package TensorFlow, which demonstrates a much straightforward way to solve optimization problems in computational imaging, and endows our program great flexibility and portability

Lanthanide-Binding Tags for 3D X‑ray Imaging of Proteins in Cells at Nanoscale Resolution

We report the application of lanthanide-binding tags (LBTs) for two- and three-dimensional X-ray imaging of individual proteins in cells with a sub-15 nm beam. The method combines encoded LBTs, which are tags of minimal size (ca. 15–20 amino acids) affording high-affinity lanthanide ion binding, and X-ray fluorescence microscopy (XFM). This approach enables visualization of LBT-tagged proteins while simultaneously measuring the elemental distribution in cells at a spatial resolution necessary for visualizing cell membranes and eukaryotic subcellular organelles

A three-dimensional thalamocortical dataset for characterizing brain heterogeneity: Region of Interest Annotations (Nrrd)

In this dataset, we provide a collection of images acquired from multiple brain regions that span an intact thalamocortical pathway (Agmon & Connors, 1991). The data was acquired using synchrotron X-ray microCT at 1.17 micron isotropic resolution. Along with these images, we provide annotations of regions of interest for the same images. All of the images are stored as tiffs and the annotations are stored as Nrrd files which can be easily opened in Fiji or Python and converted to other formats. The annotated images are located 58.5 microns apart (virtual section) from one another. The labels are 0-> no label; 1-> cortex; 2-> striatum; 3-> trn; 4-> vp; 5-> zona incerta; 6-> internal capsule; 7-> hypothalamus; 8-> corpus callosum

A three-dimensional thalamocortical dataset for characterizing brain heterogeneity: Microstructure Annotations (NumPy)

In this dataset, we provide a collection of images acquired from multiple brain regions that span an intact thalamocortical pathway (Agmon & Connors, 1991). Along with these images, we provide: (1) annotations of microstructures in the images that classify each pixel in the as either a: cell, myelinated axon, blood vessel, or background. All of these image volumes and annotations are stored as NumPy arrays. Pixels are labeled as follows: 0-> no label (background); 1-> vasculature; 2-> cell body; 3-> myelinated axon. Annotated images are provided for four regions of interest: Cortex, Striatum, TRN in thalamus, and the Zona Incerta (ZI)

Lanthanide-Binding Tags for 3D X‑ray Imaging of Proteins in Cells at Nanoscale Resolution

We report the application of lanthanide-binding tags (LBTs) for two- and three-dimensional X-ray imaging of individual proteins in cells with a sub-15 nm beam. The method combines encoded LBTs, which are tags of minimal size (ca. 15–20 amino acids) affording high-affinity lanthanide ion binding, and X-ray fluorescence microscopy (XFM). This approach enables visualization of LBT-tagged proteins while simultaneously measuring the elemental distribution in cells at a spatial resolution necessary for visualizing cell membranes and eukaryotic subcellular organelles