@article{DeCarlo:14a,
  author  = {De Carlo F and Gursoy D and Marone F and Rivers M and Parkinson YD and Khan F and Schwarz N and Vine DJ and Vogt S and Gleber SC and Narayanan S and Newville M and Lanzirotti T and Sun Y and Hong YP and Jacobsen C},
  title   = {Scientific Data Exchange: a schema for HDF5-based storage of raw and analyzed data},
  journal = {Journal of Synchrotron Radiation},
  year    = {2014},
  volume  = {21},
  number  = {6},
  pages  = {1224--1230}
}

@article{Vo:21,
author = {Nghia T. Vo and Robert C. Atwood and Michael Drakopoulos and Thomas Connolley},
journal = {Opt. Express},
keywords = {Digital image processing; Fluorescence tomography; Image processing; Image registration; Phase retrieval; Phase shift},
number = {12},
pages = {17849--17874},
publisher = {OSA},
title = {Data processing methods and data acquisition for samples larger than the field of view in parallel-beam tomography},
volume = {29},
month = {Jun},
year = {2021},
url = {http://www.opticsexpress.org/abstract.cfm?URI=oe-29-12-17849},
doi = {10.1364/OE.418448},
abstract = {Parallel-beam tomography systems at synchrotron facilities have limited field of view (FOV) determined by the available beam size and detector system coverage. Scanning the full size of samples bigger than the FOV requires various data acquisition schemes such as grid scan, 360-degree scan with offset center-of-rotation (COR), helical scan, or combinations of these schemes. Though straightforward to implement, these scanning techniques have not often been used due to the lack of software and methods to process such types of data in an easy and automated fashion. The ease of use and automation is critical at synchrotron facilities where using visual inspection in data processing steps such as image stitching, COR determination, or helical data conversion is impractical due to the large size of datasets. Here, we provide methods and their implementations in a Python package, named Algotom, for not only processing such data types but also with the highest quality possible. The efficiency and ease of use of these tools can help to extend applications of parallel-beam tomography systems.},
}