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

Compact arrangement for femtosecond laser induced generation of broadband hard x-ray pulses

We present a simple apparatus for femtosecond laser induced generation of X-rays. The apparatus consists of a vacuum chamber containing an off-axis parabolic focusing mirror, a reel system, a debris protection setup, a quartz window for the incoming laser beam, and an X-ray window. Before entering the vacuum chamber, the femtosecond laser is expanded with an all reflective telescope design to minimize laser intensity losses and pulse broadening while allowing for focusing as well as peak intensity optimization. The laser pulse duration was characterized by second-harmonic generation frequency resolved optical gating. A high spatial resolution knife-edge technique was implemented to characterize the beam size at the focus of the X-ray generation apparatus. We have characterized x-ray spectra obtained with three different samples: titanium, iron:chromium alloy, and copper. In all three cases, the femtosecond laser generated X-rays give spectral lines consistent with literature reports. We present a rms amplitude analysis of the generated X-ray pulses, and provide an upper bound for the duration of the X-ray pulses

A three-dimensional thalamocortical dataset for characterizing brain heterogeneity: X-ray microCT images (Tiff)

This dataset consists of 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. The full image volume is 1420 x 5805 x 720 pixels. The 720 images are split into 8 subvolumes, each containing 90 images. The images in each subvolume are stored as multipage tiffs in 8-bit format.Microstructure annotations associated with this dataset can be found at this doi:10.6084/m9.figshare.12153516.v1Region level annotations associated with this dataset can be found at this doi:10.6084/m9.figshare.12153549.v1</div

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)