https://github.com/antsx/antspy

A fast medical imaging analysis library in Python with algorithms for registration, segmentation, and more.

Science Score: 46.0%

This score indicates how likely this project is to be science-related based on various indicators:

○
CITATION.cff file
✓
codemeta.json file
Found codemeta.json file
✓
.zenodo.json file
Found .zenodo.json file
○
DOI references
✓
Academic publication links
Links to: scholar.google, pubmed.ncbi, ncbi.nlm.nih.gov
✓
Committers with academic emails
5 of 35 committers (14.3%) from academic institutions
○
Institutional organization owner
○
JOSS paper metadata
○
Scientific vocabulary similarity
Low similarity (15.9%) to scientific vocabulary

Keywords

medical-imaging neuroimaging python

Keywords from Contributors

medical-image-processing image-registration registration mri image-analysis open-science numfocus itk insight-toolkit bids

Last synced: 6 months ago · JSON representation

Repository

A fast medical imaging analysis library in Python with algorithms for registration, segmentation, and more.

Basic Info

Host: GitHub
Owner: ANTsX
License: apache-2.0
Language: Python
Default Branch: master
Homepage: https://antspyx.readthedocs.io
Size: 90.8 MB

Statistics

Stars: 760
Watchers: 14
Forks: 175
Open Issues: 45
Releases: 17

Topics

medical-imaging neuroimaging python

Created over 8 years ago · Last pushed 6 months ago

Metadata Files

Readme Contributing License Code of conduct

Advanced Normalization Tools in Python

The ANTsPy library wraps the well-established C++ biomedical image processing framework ANTs. It includes blazing-fast reading and writing of medical images, algorithms for registration, segmentation, and statistical learning, as well as functions to create publication-ready visualizations.

If you are looking to train deep learning models on medical imaging datasets, you might be interested in ANTsPyNet which provides tools for training and visualizing deep learning models.

Installation

Pre-compiled binaries

The easiest way to install ANTsPy is via the latest pre-compiled binaries from PyPI.

bash pip install antspyx Or alternatively from conda:

bash conda install conda-forge::antspyx

Because of limited storage space, pip binaries are not available for every combination of python version and platform. We also have had to delete older releases to make space. If you cannot find a binary you need on PyPI, you can check the Releases page for archived binaries.

Some Mac OS Python installations have compatibility issues with the pre-compiled binaries. This means pip will not install binaries targeted for the current Mac OS version, and will instead try to compile from source. The compatibility checks can be disabled by setting the environment variable SYSTEM_VERSION_COMPAT=0. More details on the wiki.

Windows users will need a compatible Microsoft Visual C++ Redistributable installation.

Building from source

In some scenarios, it can make sense to build from source. In general, you can build ANTsPy as you would any other Python package.

git clone https://github.com/antsx/antspy cd antspy python -m pip install .

Further details about installing ANTsPy or building it from source can be found in the Installation Tutorial.

Quickstart

Here is a basic overview of some of the things you can do with ANTsPy. The main functionality includes reading / writing images, basic and advanced image operations, segmentation, registration, and visualization.

```python import ants

read / write images

img = ants.imageread('path/to/image.nii.gz') ants.imagewrite(img, 'path/to/image.nii.gz')

basic operations

img + img2 img - img2 img[:20,:20,:20] # indexing returns an image

advanced operations

img = ants.smoothimage(img, 2) img = ants.resampleimage(img, (3,3,3)) img.smoothimage(2).resampleimage((3,3,3)) # chaining

convert to or from numpy

arr = img.numpy() img2 = ants.from_numpy(arr * 2)

segmentation

result = ants.atropos(a=img, m='[0.2,1x1]', c='[2,0]', i='kmeans[3]', x=ants.get_mask(img))

registration

result = ants.registration(fixedimage, movingimage, typeoftransform = 'SyN' )

plotting

ants.plot(img, overlay = img > img.mean()) ```

Tutorials

Resources for learning about ANTsPy can be found in the tutorials folder. A selection of especially useful tutorials is presented below.

Basic overview [Link]
Composite registrations [Link]
Multi-metric registration [Link]
Image math operations [Link]
Wrapping ITK code [Link]

More tutorials can be found in the ANTs repository.

Contributing

If you have a question or bug report the best way to get help is by posting an issue on the GitHub page. We welcome any new contributions and ideas. If you want to add code, the best way to get started is by reading the contributors guide that runs through the structure of the project and how we go about wrapping ITK and ANTs code in C++.

You can support our work by starring the repository, citing our methods when relevant, or suggesting new features in the issues tab. These actions help increase the project's visibility and community reach.

References

The main references can be found at the main ANTs repo. A Google Scholar search also reveals plenty of explanation of methods and evaluation results by the community and by ourselves.

Owner

Name: Advanced Normalization Tools Ecosystem
Login: ANTsX
Kind: organization
Location: Cambridge, MA; Philadelphia, PA; Southern California

Website: https://www.ants.dev
Repositories: 8
Profile: https://github.com/ANTsX

Ecosystem supporting multi-modality biomedical image analysis across programming languages.

GitHub Events

Total

Fork event: 13
Create event: 52
Commit comment event: 9
Release event: 2
Issues event: 98
Watch event: 119
Delete event: 43
Issue comment event: 311
Push event: 135
Pull request review event: 12
Pull request review comment event: 11
Gollum event: 5
Pull request event: 126

Last Year

Fork event: 13
Create event: 52
Commit comment event: 9
Release event: 2
Issues event: 98
Watch event: 119
Delete event: 43
Issue comment event: 311
Push event: 135
Pull request review event: 12
Pull request review comment event: 11
Gollum event: 5
Pull request event: 126

Committers

Last synced: 9 months ago

All Time

Total Commits: 1,729
Total Committers: 35
Avg Commits per committer: 49.4
Development Distribution Score (DDS): 0.697

Past Year

Commits: 119
Committers: 9
Avg Commits per committer: 13.222
Development Distribution Score (DDS): 0.437

Top Committers

Name	Email	Commits
ncullen93	n**h@d**u	524
stnava	s**a@g**m	431
Ravnoor Gill	r**r@g**m	216
Nick Tustison	n**n@g**m	161
Philip Cook	c**a@p**u	154
ncullen93	n**n@m**e	130
muschellij2	m**2@g**m	43
Daniel Gomez	d**z@p**g	14
Jennings Zhang	j**h@p**m	14
Andrew Berger	a**r@g**m	6
seogier	s**r@g**m	3
Thiago Franco de Moraes	t**e@g**m	3
Glad Mihai	g**i@a**m	2
sai8951	s**a@g**m	2
Vasco Diogo	3****a	2
Asaph Zylbertal	3****l	2
Bryn Lloyd	d****b	2
Dean Rance	d**4@g**m	2
Pradeep Reddy Raamana	r**p@p**u	2
Evert de Man	e**n@p**m	1
Martin Schober	m**r@f**e	1
Philipp Stephan	p**n@m**e	1
Richard Beare	R**e@m**u	1
Sadegh	s**i@g**m	1
Dženan Zukić	d**c@k**m	1
FeynmanDNA	2****A	1
Jirka Borovec	B****a	1
Oscar Esteban	c**e@o**s	1
Patrick Scheibe	p**k@h**e	1
Robert Haase	h****f	1
and 5 more...

Committer Domains (Top 20 + Academic)

gmx.de: 1 hotmail.it: 1 halirutan.de: 1 oscaresteban.es: 1 kitware.com: 1 monash.edu: 1 mediaire.de: 1 fz-juelich.de: 1 pitt.edu: 1 aicura-medical.com: 1 posteo.org: 1 med.lu.se: 1 pennmedicine.upenn.edu: 1 dartmouth.edu: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 264
Total pull requests: 413
Average time to close issues: 7 months
Average time to close pull requests: 9 days
Total issue authors: 150
Total pull request authors: 27
Average comments per issue: 4.34
Average comments per pull request: 1.51
Merged pull requests: 325
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 69
Pull requests: 130
Average time to close issues: 6 days
Average time to close pull requests: 3 days
Issue authors: 43
Pull request authors: 9
Average comments per issue: 2.41
Average comments per pull request: 1.59
Merged pull requests: 113
Bot issues: 0
Bot pull requests: 0

View more stats

Top Authors

Issue Authors

cookpa (34)
ntustison (11)
rueberger (11)
ncullen93 (6)
dipterix (6)
samtorrisi (5)
stnava (5)
dyollb (4)
FIrgolitsch (4)
ninusch (4)
poldrack (3)
galenlynch (3)
amirreza1998 (3)
yuanpengpeng (2)
QuentinMesnildrey (2)

Pull Request Authors

cookpa (205)
ncullen93 (91)
ntustison (69)
ravnoor (6)
sai8951 (4)
rueberger (4)
dyollb (4)
seogier (2)
DeanTM (2)
dzenanz (2)
FeynmanDNA (2)
lankabelgezogen (2)
evertdeman (2)
crossmanith (2)
sarthakpati (2)

Top Labels

Issue Labels

distribution (8) help wanted (7) enhancement (5) bug (5) feature request (4) would be nice (2) code (2) question (2) dependencies (1)

Pull Request Labels

help wanted (1)

Packages

Total packages: 1
Total downloads:
- pypi 19,961 last-month
Total docker downloads: 3,976

Total dependent packages: 23
Total dependent repositories: 41
Total versions: 13
Total maintainers: 4

pypi.org: antspyx

A fast medical imaging analysis library in Python with algorithms for registration, segmentation, and more.

Homepage: https://github.com/antsx/antspy
Documentation: https://antspyx.readthedocs.io/
License: Apache Software License
Latest release: 0.6.1
published 8 months ago

Versions: 13
Dependent Packages: 23
Dependent Repositories: 41
Downloads: 19,961 Last month
Docker Downloads: 3,976

Rankings

Dependent packages count: 0.7%

Docker downloads count: 1.6%

Dependent repos count: 2.3%

Average: 2.4%

Stargazers count: 2.8%

Downloads: 3.2%

Forks count: 4.0%

Maintainers (4)

stnava ntustison rvnr cookpa

Last synced: 6 months ago

Dependencies

docs/requirements.txt pypi

sphinx *

requirements.txt pypi

Pillow *
matplotlib *
nibabel *
numpy *
pandas *
pyyaml *
scikit-image *
scikit-learn *
sklearn *
statsmodels *
webcolors *

setup.py pypi

Pillow *
chart_studio *
matplotlib *
nibabel *
numpy *
pandas *
pyyaml *
scikit-image *
scikit-learn *
scipy *
statsmodels *
webcolors *

environment.yml conda

matplotlib
numpy
pandas
pillow
pip
pyyaml
scikit-image
scikit-learn
statsmodels

.github/workflows/ci-docker.yml actions

actions/checkout v2 composite
docker/build-push-action v3 composite
docker/login-action v1 composite
docker/metadata-action v3 composite
docker/setup-buildx-action v2 composite
docker/setup-qemu-action v2 composite

.github/workflows/wheels.yml actions

actions/checkout v3 composite
actions/setup-python v4 composite
actions/upload-artifact v3 composite
ilammy/msvc-dev-cmd v1 composite

Dockerfile docker

continuumio/miniconda3 22.11.1 build
debian bullseye-20230109-slim build

rtd_requirements.txt pypi

sphinx ==6.2.1

https://github.com/antsx/antspy

Science Score: 46.0%

Keywords

Keywords from Contributors

Repository

Basic Info

Statistics

Topics

Metadata Files

README.md

Advanced Normalization Tools in Python

Installation

Pre-compiled binaries

Building from source

Quickstart

read / write images

basic operations

advanced operations

convert to or from numpy

segmentation

registration

plotting

Tutorials

Contributing

References

Owner

GitHub Events

Total

Last Year

Committers

All Time

Past Year

Top Committers

Committer Domains (Top 20 + Academic)

Issues and Pull Requests

All Time

Past Year

Top Authors

Issue Authors

Pull Request Authors

Top Labels

Issue Labels

Pull Request Labels

Packages

pypi.org: antspyx

Rankings

Maintainers (4)

Dependencies