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Clinica

Software platform for clinical neuroscience studies

What is Clinica?

Clinica is a software platform for clinical neuroscience research studies, i.e. studies involving patients with neurological and psychiatric diseases, using multimodal data (neuroimaging, clinical and cognitive evaluations, genetics...) and most often longitudinal follow-up.

Clinica is developed by the ARAMIS Lab at the ICM in Paris.

What are the main features of Clinica?

Neuroimaging data analysis:
• Anatomical MRI
• Diffusion MRI
• PET
• more modalities soon to come!

Statistical analysis

Machine learning

Data management made easy:
• Standardized data structures for inputs
• Standardized data structures for outputs
• Conversion of data sets

Which technologies underlie Clinica?

Clinica is written in Python.

It uses the Nipype system for pipelining. It combines widely-used software for neuroimaging data analysis (SPM, FreeSurfer, FSL, MRtrix, ...), machine learning (Scikit-learn) and the BIDS standard for data organization.

What are the benefits of using Clinica and not simply those widely-used software?

In short: to make your life easier.

Specifically, Clinica provides:
• complex processing pipelines involving combination of different analysis software
• integration between feature extraction and statistics/machine learning
• standardized file organization

This should help you to:
• easily share data and results within your institution and with external collaborators
• make your research more reproducible
• spend less time on data management and processing

Mobirise

Olivier Colliot

• Project coordinator
• Co-founder

Mobirise

Stanley Durrleman

• Co-founder

Mobirise

Michael Bacci

• Software Architecture
• Optimizations
• Command-line System
• Test / Benchmarks / Profiling

Mobirise

Simona Bottani

• Atlas-based measurements
• Machine learning
• Data converters (AIBL)

Mobirise

Ninon Burgos

• PET data analysis
• Test / Benchmarks / Profiling
• Project management
• Documentation

Mobirise

Sabrina Fontanella

• I/O
• Data converters (ADNI, AIBL, OASIS)
• Data structure specifications

Mobirise

Pietro Gori

• Approximation of white matter bundles (future release)

Mobirise

Jérémy Guillon

• Software Architecture
• Optimizations
• Functional MRI analysis

Mobirise

Thomas Jacquemont

• Diffusion MRI analysis
• Atlas-based measurements

Mobirise

Pascal Lu

• Genetic data analysis (future release)
• Machine learning

Mobirise

Arnaud Marcoux

• PET data analysis
• Test / Benchmarks / Profiling

Mobirise

Tristan Moreau

• Diffusion MRI analysis

Alexandre Routier

Alexandre Routier

• Software Architecture
• Anatomical MRI analysis
• Diffusion MRI analysis
• Surface-based statistics
• CAPS data structure specifications
• Project management
• Documentation
• Website
• Test / Benchmarks / Profiling

Mobirise

Jorge Samper-Gonzalez

• Anatomical MRI analysis
• PET data analysis
• Machine learning
• Data converters (ADNI)
• Test / Benchmarks / Profiling

Mobirise

Junhao Wen

• Anatomical MRI analysis
• Surface-based statistics
• Test / Benchmarks / Profiling

  • T. Jacquemont, F. De Vico Fallani, A. Bertrand, S. Epelbaum, A. Routier, B. Dubois, H. Hampel, S. Durrleman, O. Colliot - Amyloidosis and neurodegeneration result in distinct structural connectivity patterns in mild cognitive impairment. Neurobiology of Aging, Elsevier, 2017. Access the paper!
  • N. Burgos, J. Samper-González, A. Bertrand, M-O. Habert, S. Ourselin, S. Durrleman, M. J. Cardoso, O. ColliotIndividual Analysis of Molecular Brain Imaging Data Through Automatic Identification of Abnormality Patterns. Computational Methods for Molecular Imaging - [MICCAI 2017 Satellite Workshop], 2017. Access the paper!    
  • J. Samper-Gonzalez, N. Burgos, F. Sabrina, H. Bertin, M-O. Habert, S. Durrleman, T. Evgeniou, O. ColliotYet Another ADNI Machine Learning Paper? Paving The Way Towards Fully-reproducible Research on Classification of Alzheimer's Disease. Machine Learning in Medical Imaging - MICCAI 2017 Satellite Workshop, 2017. Access the paper!
  • Many more to come!


Clinica is a software for research studies. It is not intended for use in medical routine

About ARAMIS Lab

ARAMIS Lab is a pluridisciplinary group bringing together methodological researchers (computer science, applied mathematics) and medical experts (neurology, medical imaging).

Adress

ICM
Équipe Aramis, 3eme étage
Hôpital de la Pitié-Salpêtrière
47, boulevard de l’hôpital
75013 Paris
France

Support

Mobirise

Copyright (c) 2016-2017 Clinica