Contributors and citation

Contributors and citation#

bartorch is developed by its contributors (git shortlog -sne HEAD in a clone) and builds on the work of the BART developers, whose history is that of the external/bart submodule. Developer guide describes how to contribute.

Citing bartorch#

bartorch has no publication and no archival DOI. Work that uses it cites BART, the backends that computed its results, and the methods it applied, and reports the software versions:

  • BART: Uecker M, Ong F, Tamir JI, Bahri D, Virtue P, Cheng JY, Zhang T, Lustig M. Berkeley Advanced Reconstruction Toolbox. Proc Intl Soc Mag Reson Med 23:2486 (2015); and the Zenodo record of the BART version used, reached from doi:10.5281/zenodo.592960. BART asks that the articles corresponding to the methods used be cited as well; its doc/references.txt lists them.

  • Methods: the publications of the reconstruction methods used, for example SENSE, ESPIRiT, compressed sensing or nonlinear inversion; the References sections of the explanation pages and examples list them.

  • Non-uniform FFT, for non-Cartesian data: Barnett AH, Magland J, af Klinteberg L. A parallel nonuniform fast Fourier transform library based on an “exponential of semicircle” kernel. SIAM J Sci Comput 41(5):C479-C504 (2019), doi:10.1137/18M120885X; and, for CUDA tensors, Shih Y, Wright G, Andén J, Blaschke J, Barnett AH. cuFINUFFT: a load-balanced GPU library for general-purpose nonuniform FFTs. IEEE IPDPSW 688-697 (2021), doi:10.1109/IPDPSW52791.2021.00105.

Reproducibility#

A reproducible report states:

Item

Source

bartorch version or commit

bartorch.__version__, git rev-parse HEAD

BART revision

bartorch.bart_version(); git -C external/bart rev-parse HEAD in a source build

Build and backends

bartorch.build_info(), bartorch.backend_sources(), the FINUFFT and cuFINUFFT versions

Device

CPU or GPU model, driver and CUDA versions

Data conventions

Array order, trajectory units, Fourier-transform centring and normalization

Calibration and sampling

Sensitivity estimation, sampling pattern or trajectory

Solver settings

Algorithm, iterations, step size, regularization terms and weights, data scaling