Evolution of hierarchical phase-contrast tomography on the European Synchrotron beamlines BM05 and BM18: a whole adult human brain imaging case study.

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Paper

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The authors' code

Shell · 204 lines · 6.3 KB · no license

#!/bin/bash
set -ex
cuda_activate="module load cuda/11.8"
$cuda_activate
TAG=beyond_tetra
INST_DIR=/tmp_14_days/mirone/
ENV_DIR=${INST_DIR}/beyondtetra_merge
PYTHON_VERSION="3.8"
NABU_WHEELHOUSE="http://www.silx.org/pub/nabu/wheels/numpy2"
python${PYTHON_VERSION} -m venv $ENV_DIR
sed -i "3s|^|${cuda_activate}\\n|" "$ENV_DIR/bin/activate"
sed -i '3s/^/export SKIP_TOMOSCAN_CHECK=\"1\" \n/' $ENV_DIR/bin/activate
sed -i '3s/^/export TOMOTOOLS_SKIP_DET_CHECK=\"1\" \n/' $ENV_DIR/bin/activate
source $ENV_DIR/bin/activate
pip install pip --upgrade
# ---------------------------------
# BASE LAYER
# ---------------------------------
#. Some standard package
pip install numpy scipy matplotlib ipython h5py jupyterlab
pip install gnureadline
# ~~~~~~ global so that the cmake helpers are available ~~~~~~~~~~~~~~~
pip install pybind11[global]
# ~~~~~~~ this helps cmake to find where pybind11 from pip can be found ~~~~~~~~~~~~
export CMAKE_PREFIX_PATH="$(python -m pybind11 --cmakedir)"
#. Remaining possibly via trusted-host
PIP_OPTIONS="--trusted-host www.silx.org --find-links $NABU_WHEELHOUSE --prefer-binary"
pip install --no-cache-dir $PIP_OPTIONS pycuda pyvkfft
pip install hdf5plugin
# pip install $PIP_OPTIONS scikit-image
pip install scikit-image
pip install silx==1.1.2
pip install pyunitsystem==1.1.1
python3 -m pip install git+https://gitlab.esrf.fr/mirone/nxtomomill@nr_25_06_06 --no-deps --force
python3 -m pip install git+https://gitlab.esrf.fr/mirone/nxtomo@nr_25_06_06 --no-deps --force
python3 -m pip install git+https://gitlab.esrf.fr/mirone/tomoscan@nr_25_06_06 --no-deps --force
pip install dicttoxml==1.7.16
# if [ "$(uname -m)" == "x86_64" ]; then
# pip install $PIP_OPTIONS pyopencl
# pip install cupy-cuda11x
# pip install algotom
# pip install "jupyterlab" "batchspawner==1.3.0" "jupyterhub==4.1.5"
# pip install spam[graphical]
# fi
# tomotools base layer
# pip install "tomoscan[full]" --pre
# pip install "nxtomo[full]" --pre
# pip install "nxtomomill[full]" --pre
# get the last nxtomomill still working with python3.8
# python3 -m pip install git+https://gitlab.esrf.fr/tomotools/nxtomomill@0.10
# nedded for night_rail
pip install pybind11
pip install pandas scipy
pip install pyperclip
pip install dateparser
# night_rail
python3 -m pip install git+https://gitlab.esrf.fr/night_rail/night_rail@${TAG} --no-deps --force
python3 -m pip install git+https://gitlab.esrf.fr/night_rail/applications/mirone/night_rail_bm18@${TAG} --no-deps --force
export CMAKE_ARGS="-DPython3_NumPy_INCLUDE_DIR=$(python -c 'import numpy,os;print(os.path.join(os.path.dirname(numpy.__file__), "core", "include"))')"
set +e
python3 -m pip install git+https://gitlab.esrf.fr/night_rail/applications/tools/nabuxx@${TAG} --no-deps --force -vvv
set -e
python3 -m pip install git+https://gitlab.esrf.fr/night_rail/applications/tools/etfscan@${TAG} --no-deps --force
python3 -m pip install git+https://gitlab.esrf.fr/mirone/nabu@${TAG} --no-deps --force
python3 -m pip install git+https://gitlab.esrf.fr/night_rail/applications/tools/double_flats@$TAG --no-deps --force
# for the interface
pip install git+https://gitlab.esrf.fr/icat/pyicat-plus@main
pip install openpyxl
# this is used in the getdoubles package
pip install opencv-python
pip install numexpr
pip install bottleneck
pip install silx==1.1.2
pip install pyunitsystem==1.1.1
python3 -m pip install git+https://gitlab.esrf.fr/mirone/nxtomomill@nr_25_06_06 --no-deps --force
python3 -m pip install git+https://gitlab.esrf.fr/mirone/nxtomo@nr_25_06_06 --no-deps --force
python3 -m pip install git+https://gitlab.esrf.fr/mirone/tomoscan@nr_25_06_06 --no-deps --force
### MAKING TAG AVAILABLE
# 0. go into a clean directory
unique_dir=$(mktemp -d -p /tmp)
cd $unique_dir
# 1. Correctly get the installation directory of the installed night_rail_bm18 module
module_dir=$(python -c "import sys, night_rail_bm18, os; sys.path = list(filter(None, sys.path)); print(os.path.dirname(night_rail_bm18.__file__))")
if [ -z "$module_dir" ]; then
echo "Unable to locate the directory for the module night_rail_bm18."
exit 1
fi
echo "Module directory: $module_dir"
# 2. Create (or overwrite) tag.py in the module's directory, setting the tag variable
echo "tag = '$TAG'" > "${module_dir}/tag.py"
echo "Created file ${module_dir}/tag.py with tag = '$TAG'"
# pip install "nabu[full]" $PIP_OPTIONS --pre
# pip install --force-reinstall --no-deps --pre nabu
# pip uninstall -y scikit-cuda || true
# pip install pandas
# # ----------------------------------------
# # NIGHT_RAIL LAYER
# # -----------------------------------------
# # pip install -r freeze_no_surprise.txt
# pip install pyperclip
# pip install dateparser
# python3 -m pip install git+https://gitlab.esrf.fr/night_rail/night_rail@${TAG} --no-deps --force
# python3 -m pip install git+https://gitlab.esrf.fr/night_rail/applications/mirone/night_rail_bm18@${TAG} --no-deps --force
# python3 -m pip install git+https://gitlab.esrf.fr/night_rail/applications/tools/nabuxx@${TAG} --no-deps --force
# python3 -m pip install git+https://gitlab.esrf.fr/night_rail/applications/tools/etfscan@${TAG} --no-deps --force
# python3 -m pip install git+https://gitlab.esrf.fr/mirone/nabu@${TAG} --no-deps --force
# # python3 -m pip install git+https://gitlab.esrf.fr/mirone/aspect_phase_comppag@$TAG --no-deps --force
# python3 -m pip install git+https://gitlab.esrf.fr/night_rail/applications/tools/double_flats@$TAG --no-deps --force
# #~~~~~~~ auxiliary packages
# pip install git+https://gitlab.esrf.fr/icat/pyicat-plus@main
# pip install openpyxl
# # this is used in the getdoubles package
# pip install opencv-python
# pip install numexpr
# ### MAKING TAG AVAILABLE
# # 0. go into a clean directory
# unique_dir=$(mktemp -d -p /tmp)
# cd $unique_dir
# # 1. Correctly get the installation directory of the installed night_rail_bm18 module
# module_dir=$(python -c "import sys, night_rail_bm18, os; sys.path = list(filter(None, sys.path)); print(os.path.dirname(night_rail_bm18.__file__))")
# if [ -z "$module_dir" ]; then
# echo "Unable to locate the directory for the module night_rail_bm18."
# exit 1
# fi
# echo "Module directory: $module_dir"
# # 2. Create (or overwrite) tag.py in the module's directory, setting the tag variable
# echo "tag = '$TAG'" > "${module_dir}/tag.py"
# echo "Created file ${module_dir}/tag.py with tag = '$TAG'"

no_surprise_installation_script_u20.sh at commit f30b9e7, no license · at the source

Overview

Authors: Hector Dejea¹, Joseph Brunet^1,2, Theresa Urban^1,2, Camille Berruyer^1,2, Alessandro Mirone¹, Christoph Jarnias¹, Alexandre Bellier³, Claire Walsh², Peter D. Lee², Paul Tafforeau¹

ORCID iDs: Hector Dejea, Joseph Brunet, Theresa Urban, Camille Berruyer, Alexandre Bellier, Claire Walsh, Peter D. Lee, Paul Tafforeau

Institutions: European Synchrotron Radiation Facility (France); University College London (United Kingdom); Université Grenoble Alpes (France)

Journal: Journal of synchrotron radiation, volume 33, issue Pt 4, pages 1180-1189

Dates: received 15 January 2026; accepted 25 May 2026; published online 19 June 2026; in print July 2026

Type: Research article · Language: English

License: CC BY

Identifiers: DOI 10.1107/s1600577526005503 · PMID 42319807 · PMCID PMC13344596 · OpenAlex W7165411206

Open access: gold, a free copy (OpenAlex)

Status: code verified

Categories: human (organism)

Methods: Connectivity

Keywords: human brain, synchrotron, phase-contrast tomography, whole-organ imaging

MeSH: Brain*, Synchrotrons*, Tomography, X-Ray Computed*, Adult, Humans (* major topic)

Topic: Advanced X-ray Imaging Techniques (Radiation, Physics and Astronomy), according to OpenAlex

Funding: Chan Zuckerberg Initiative (CZI) (DAF2020-225394, DAF2022-316777); European Synchrotron Radiation Facility (md1252, md1290, md1389); Royal Academy of Engineering (CiET1819/10); UK Medical Research Council (MR/R025673/1); Canadian Institute for Advanced Research

Citations: not cited yet (Europe PMC); 57 references in the paper

Abstract

Hierarchical phase-contrast tomography (HiP-CT) was recently developed to enable the ex vivo imaging of human organs at multiple scales from whole organ down to near-cellular resolution in localized regions. Using whole adult human brain imaging as a case study, this article shows the evolution and optimization of this technique from its initial development at the BM05 beamline to its transition and current status at BM18. Thanks to the higher spatial coherence, larger beam size, higher energies and larger propagation distances available at BM18 and due to the European Synchrotron’s Extremely Brilliant Source upgrade (ESRF-EBS), this transition resulted in significantly improved data quality, resolution, sensitivity and speed. More recently, the implementation of a new generation of larger sCMOS cameras, helical scanning (including dedicated reconstruction algorithm developments), binning at the chip and projections levels, and the design of high-efficiency optics allowed us to progressively improve the trade-off between dose and image quality, and acquisition time. These advances enable whole-organ imaging at voxel sizes ranging from ∼42 µm to ∼15 µm, with acquisition times reduced from ∼18 h to ∼3–6 h, depending on configuration. These acquisition schemes present the current status of full-organ imaging using HiP-CT and represent the constant efforts for improvement of the technique towards the investigation of human organs in health, disease and ageing.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repository

Its files are read in the Code ↔ Paper reader above.

gitlab.esrf.fr/night_rail/applications/mirone/night_rail_bm18

License: none: the authors keep all their rights

State: the link answers, verified on 27 September 2026

Evidence: files inventoried

Commit: f30b9e7ffc521595e17e28f7476b22ee1b5dec29, 25 August 2026

Languages: Python (99), Shell (7), C++ (1)

Size: 115 files, 107 scripts

Software Heritage: not archived

Found in: the references

Holds: README, environment (setup.py), tests, documentation

Not found: license file, CITATION.cff, continuous integration

Tools: NumPy (50 files), h5py (45 files), SciPy (14 files), Matplotlib (12 files), tifffile (12 files), OpenCV (4 files), Pillow (3 files), pandas (2 files), scikit-image (2 files), Numba (1 file)

Availability: 1 check, the latest on 27 September 2026: the link answers

27 September 2026: the link answers

108 files

install_u20_venv/no_surprise_installation_script_u20.sh, Shell, 204 lines
install_u24_venv/no_surprise_installation_script_u24.sh, Shell, 729 lines
install_u24_venv/validation/test_no_surprise_configuration.py, Python, 147 lines
install_u24_venv/validation/validate_hdf5_filters.py, Python, 191 lines
install_u24_venv/validation/validate_nightrail_install.py, Python, 194 lines
night_rail_bm18/__init__.py, Python, 1 line
night_rail_bm18/app/__init__.py, Python, 1 line
night_rail_bm18/app/automatic.py, Python, 725 lines
night_rail_bm18/app/automatic_gui.py, Python, 1,268 lines
night_rail_bm18/app/colla.py, Python, 431 lines
night_rail_bm18/app/create_scripts.py, Python, 340 lines
night_rail_bm18/app/create_scripts_distortion.py, Python, 82 lines
night_rail_bm18/app/cutscan.py, Python, 149 lines
night_rail_bm18/app/deploy_batch_defaults.py, Python, 158 lines
night_rail_bm18/app/diffusion_fit.py, Python, 1,232 lines
night_rail_bm18/app/extract_lines_general.py, Python, 590 lines
night_rail_bm18/app/find_scan_substitute.py, Python, 271 lines
night_rail_bm18/app/fitpoly_correction_map.py, Python, 496 lines
night_rail_bm18/app/fix_incoherent_scan_size.py, Python, 300 lines
night_rail_bm18/app/graph_runner.py, Python, 145 lines
night_rail_bm18/app/hdf5_to_jp2k.py, Python, 141 lines
night_rail_bm18/app/join_lines.py, Python, 104 lines
night_rail_bm18/app/libs_for_automatic/__init__.py, Python, 1 line
night_rail_bm18/app/libs_for_automatic/scan_utils.py, Python, 785 lines
night_rail_bm18/app/libs_for_automatic/utils_for_automatic.py, Python, 1,325 lines
night_rail_bm18/app/manage_imagej.sh, Shell, 116 lines
night_rail_bm18/app/mend_single_scan.py, Python, 157 lines
night_rail_bm18/app/modify_wf_json.py, Python, 66 lines
night_rail_bm18/app/nexus_juicer.py, Python, 669 lines
night_rail_bm18/app/plot_cor_vs_z.py, Python, 73 lines
night_rail_bm18/app/polyfit_cors.py, Python, 80 lines
night_rail_bm18/app/prepare_online.py, Python, 797 lines
night_rail_bm18/app/print_affinity_cpu_count.py, Python, 12 lines
night_rail_bm18/app/ricostruisci_da_sinogramma.py, Python, 177 lines
night_rail_bm18/app/setup_pars.py, Python, 91 lines
night_rail_bm18/app/setup_pars_distortion.py, Python, 76 lines
night_rail_bm18/app/to_htj2k.py, Python, 5 lines
night_rail_bm18/app/to_htj2k_hdf5.py, Python, 86 lines
night_rail_bm18/app/to_jp2.py, Python, 422 lines
night_rail_bm18/app/to_tiff.py, Python, 585 lines
night_rail_bm18/app/to_zarr.py, Python, 242 lines
night_rail_bm18/decisional_trees/__init__.py, Python, 1 line
night_rail_bm18/decisional_trees/distortion_calibration_rec_tree.py, Python, 596 lines
night_rail_bm18/decisional_trees/distortion_calibration_scripts.py, Python, 961 lines
night_rail_bm18/decisional_trees/rec_tree.py, Python, 2,642 lines
night_rail_bm18/decisional_trees/scintdeconv.py, Python, 198 lines
night_rail_bm18/decisional_trees/scripts.py, Python, 3,214 lines
night_rail_bm18/decisional_trees/utils.py, Python, 310 lines
night_rail_bm18/movement_correction/__init__.py, Python, 27 lines
night_rail_bm18/movement_correction/basins_and_regions.py, Python, 1,004 lines
night_rail_bm18/movement_correction/fit_reference_shape.py, Python, 1,157 lines
night_rail_bm18/movement_correction/fit_region_offset.py, Python, 951 lines
night_rail_bm18/movement_correction/metrics.py, Python, 166 lines
night_rail_bm18/movement_correction/profile_report.py, Python, 136 lines
night_rail_bm18/movement_correction/region_labels.py, Python, 194 lines
night_rail_bm18/movement_correction/roi_crops.py, Python, 188 lines
night_rail_bm18/movement_correction/scan_profile.py, Python, 160 lines
night_rail_bm18/movement_correction/select_regions.py, Python, 453 lines
night_rail_bm18/movement_correction/stack_crops.py, Python, 97 lines
night_rail_bm18/movement_correction/stack_full_binned.py, Python, 132 lines
night_rail_bm18/movement_correction/stack_roi_per_z.py, Python, 131 lines
night_rail_bm18/movement_correction/standard_flow.py, Python, 1,206 lines
night_rail_bm18/movement_correction/test_region_split.py, Python, 244 lines
night_rail_bm18/movement_correction/verify_geometry.py, Python, 218 lines
night_rail_bm18/slurm_header.py, Python, 383 lines
night_rail_bm18/utilities/__init__.py, Python, 1 line
night_rail_bm18/utilities/companion_file_templating.py, Python, 367 lines
night_rail_bm18/utils.py, Python, 56 lines
no_surprise_installation_script.sh, Shell, 85 lines
sandbox/adjust_lut.py, Python, 79 lines
sandbox/center_of_mas_wobble/media_amppiezze.py, Python, 65 lines
sandbox/center_of_mas_wobble/processa_alignement.py, Python, 189 lines
sandbox/center_of_mas_wobble/script2.sh, Shell, 12 lines
sandbox/change_time.py, Python, 27 lines
sandbox/copia.py, Python, 91 lines
sandbox/count.py, Python, 4 lines
sandbox/double_junction.py, Python, 375 lines
sandbox/extract_lut.py, Python, 385 lines
sandbox/extract_lut_noinitiallinearity.py, Python, 598 lines
sandbox/fitmap/fitta_all.py, Python, 276 lines
sandbox/fitmap/fitta_map_a.py, Python, 249 lines
sandbox/fitmap/fitta_map_b.py, Python, 251 lines
sandbox/fitmap/ricostruisci_da_sinogramma_a.py, Python, 209 lines
sandbox/fitmap/ricostruisci_da_sinogramma_b.py, Python, 181 lines
sandbox/flatten_structure.py, Python, 224 lines
sandbox/flatten_structure_hregrouped.py, Python, 514 lines
sandbox/generate_compression_comparison_beamer.py, Python, 577 lines
sandbox/intersezioni.py, Python, 57 lines
sandbox/make_overlap_crops_fullheight.py, Python, 763 lines
sandbox/night_rail_bm18_collect_batch_tiffs.sh, Shell, 14 lines
sandbox/night_rail_bm18_copy_by_link.sh, Shell, 180 lines
sandbox/parallel_inverti.py, Python, 167 lines
sandbox/splitter.py, Python, 114 lines
sandbox/stack_centerline.cpp, C++, 389 lines
sandbox/to_zarr.py, Python, 150 lines
sandbox/tojp2k.py, Python, 262 lines
sandbox/tojp2k_images.py, Python, 197 lines
setup.py, Python, 102 lines
test/run_all.py, Python, 225 lines
test/test_epr_material_from_file.py, Python, 188 lines
test/test_epr_n_iters1.py, Python, 97 lines
test/test_hdf5_plugin_path_callers.py, Python, 135 lines
test/test_jpeg2000_parameters.py, Python, 57 lines
test/test_near_cor_mapping.py, Python, 64 lines
test/test_z_series_external_refs.py, Python, 82 lines
utilities/all2hdf5.py, Python, 34 lines
utilities/temp2inp.py, Python, 10 lines
README.rst, Text, 761 lines

At the source: gitlab.esrf.fr/night_rail/applications/mirone/night_rail_bm18

Tracing map

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107 scripts, each with its path and the digest of its content;
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Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 10 authors, 4 keywords, 5 MeSH terms, 5 funders, 42 references.

Cite

This paper

Dejea, H., Brunet, J., Urban, T., Berruyer, C., Mirone, A., Jarnias, C., Bellier, A., Walsh, C., Lee, P. D., & Tafforeau, P. (2026). Evolution of hierarchical phase-contrast tomography on the European Synchrotron beamlines BM05 and BM18: a whole adult human brain imaging case study. Journal of synchrotron radiation, 33(Pt 4), 1180-1189. https://doi.org/10.1107/s1600577526005503

BibTeX

@article{dejea2026evolution, author = {Dejea, Hector and Brunet, Joseph and Urban, Theresa and Berruyer, Camille and Mirone, Alessandro and Jarnias, Christoph and Bellier, Alexandre and Walsh, Claire and Lee, Peter D. and Tafforeau, Paul}, title = {{Evolution of hierarchical phase-contrast tomography on the European Synchrotron beamlines BM05 and BM18: a whole adult human brain imaging case study}}, journal = {Journal of synchrotron radiation}, year = {2026}, month = jun, volume = {33}, number = {Pt 4}, pages = {1180--1189}, publisher = {International Union of Crystallography}, issn = {0909-0495}, doi = {10.1107/s1600577526005503}, url = {https://doi.org/10.1107/s1600577526005503}, pmid = {42319807}, pmcid = {PMC13344596} }

RIS

TY - JOUR AU - Dejea, Hector AU - Brunet, Joseph AU - Urban, Theresa AU - Berruyer, Camille AU - Mirone, Alessandro AU - Jarnias, Christoph AU - Bellier, Alexandre AU - Walsh, Claire AU - Lee, Peter D. AU - Tafforeau, Paul TI - Evolution of hierarchical phase-contrast tomography on the European Synchrotron beamlines BM05 and BM18: a whole adult human brain imaging case study T2 - Journal of synchrotron radiation J2 - J Synchrotron Radiat PY - 2026 DA - 2026/06/19 VL - 33 IS - Pt 4 SP - 1180 EP - 1189 SN - 0909-0495 PB - International Union of Crystallography DO - 10.1107/s1600577526005503 UR - https://doi.org/10.1107/s1600577526005503 LA - en ER -

CSL-JSON

{ "id": "10.1107/s1600577526005503", "type": "article-journal", "title": "Evolution of hierarchical phase-contrast tomography on the European Synchrotron beamlines BM05 and BM18: a whole adult human brain imaging case study", "container-title": "Journal of synchrotron radiation", "author": [ { "family": "Dejea", "given": "Hector" }, { "family": "Brunet", "given": "Joseph" }, { "family": "Urban", "given": "Theresa" }, { "family": "Berruyer", "given": "Camille" }, { "family": "Mirone", "given": "Alessandro" }, { "family": "Jarnias", "given": "Christoph" }, { "family": "Bellier", "given": "Alexandre" }, { "family": "Walsh", "given": "Claire" }, { "family": "Lee", "given": "Peter D." }, { "family": "Tafforeau", "given": "Paul" } ], "container-title-short": "J Synchrotron Radiat", "volume": "33", "issue": "Pt 4", "page": "1180-1189", "DOI": "10.1107/s1600577526005503", "PMID": "42319807", "PMCID": "PMC13344596", "ISSN": "0909-0495", "publisher": "International Union of Crystallography", "URL": "https://doi.org/10.1107/s1600577526005503", "language": "en", "issued": { "date-parts": [ [ 2026, 6, 19 ] ] } }

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