Package: clinica
ClinicaSoftware platform for clinical neuroimaging studiesHomepage|Documentation|Paper|Forum|
  See also:AD-ML,AD-DL,ClinicaDLAbout The ProjectClinica is a software platform for clinical research studies involving patients
with neurological and psychiatric diseases and the acquisition of multimodal
data (neuroimaging, clinical and cognitive evaluations, genetics...),
most often with longitudinal follow-up.Clinica is command-line driven and written in Python.
It uses theNipypesystem for pipelining and combines
widely-used software packages for neuroimaging data analysis
(ANTs,FreeSurfer,FSL,MRtrix,PETPVC,SPM), machine learning
(Scikit-learn) and theBIDS
standardfor data organization.Clinica provides tools to convert publicly available neuroimaging datasets into
BIDS, namely:ADNI: Alzheimer’s Disease Neuroimaging InitiativeAIBL: Australian Imaging, Biomarker & Lifestyle Flagship Study of AgeingHABS: Harvard Aging Brain StudyNIFD: Neuroimaging in Frontotemporal DementiaOASIS: Open Access Series of Imaging StudiesOASIS-3: Longitudinal Neuroimaging, Clinical, and Cognitive Dataset for Normal Aging and Alzheimer’s DiseaseClinica can process any BIDS-compliant dataset with a set of complex processing
pipelines involving different software packages for the analysis of
neuroimaging data (T1-weighted MRI, diffusion MRI and PET data).
It also provides integration between feature extraction and statistics, machine
learning or deep learning.Clinica is also showcased as a framework for the reproducible classification of
Alzheimer's disease usingmachine learninganddeep learning.Getting StartedFull instructions for installation and additional information can be found in
theuser documentation.Using pipx (recommended)Clinica can be easily installed and updated usingpipx.pipx install clinicaUsing pippip install clinicaUsing CondaClinica relies on multiple third-party tools to perform processing.An environment file is provided in this repository
to facilitate their installation in aCondaenvironment:git clone https://github.com/aramis-lab/clinica && cd clinicaconda env createconda activate clinicaAfter activation, usepipto install Clinica.Additional dependencies (required)Depending on the pipeline that you want to use, you need to install pipeline-specific interfaces.
Some of which uses a different runtime or use incompatible licensing terms, which prevent their distribution alongside Clinica.
Not all the dependencies are necessary to run Clinica.
Please refer to thispageto determine which third-party libraries you need to install.ExampleDiagram illustrating the Clinica pipelines involved when performing a group
comparison of FDG PET data projected on the cortical surface between patients
with Alzheimer's disease and healthy controls from the ADNI database:Clinical and neuroimaging data are downloaded from the ADNI website and data
are converted into BIDS with theadni-to-bidsconverter.Estimation of the cortical and white surface is then produced by thet1-freesurferpipeline.FDG PET data can be projected on the subject’s cortical surface and
normalized to the FsAverage template from FreeSurfer using thepet-surfacepipeline.TSV file with demographic information of the population studied is given to
thestatistics-surfacepipelineto generate
the results of the group comparison.For more examples and details, please refer to theDocumentation.SupportCheck forpast answersin the old Clinica Google GroupStart adiscussionon GithubReport anissueon GitHubContributingWe encourage you to contribute to Clinica!
Please check out theContributing to Clinica guidefor
guidelines about how to proceed.  Do not hesitate to ask questions if something
is not clear for you, report an issue, etc.LicenseThis software is distributed under the MIT License.
Seelicense filefor more information.Citing usRoutier, A., Burgos, N., Díaz, M., Bacci, M., Bottani, S., El-Rifai O., Fontanella, S., Gori, P., Guillon, J., Guyot, A., Hassanaly, R., Jacquemont, T.,  Lu, P., Marcoux, A.,  Moreau, T., Samper-González, J., Teichmann, M., Thibeau-Sutre, E., Vaillant G., Wen, J., Wild, A., Habert, M.-O., Durrleman, S., and Colliot, O.:Clinica: An Open Source Software Platform for Reproducible Clinical Neuroscience StudiesFrontiers in Neuroinformatics, 2021doi:10.3389/fninf.2021.689675Related RepositoriesAD-DL: Classification of Alzheimer's disease status with convolutional neural networks.AD-ML: Framework for the reproducible classification of Alzheimer's disease using
machine learning.ClinicaDL: Framework for the reproducible processing of neuroimaging data with deep learning methods.