AUTHOR=Routier Alexandre , Burgos Ninon , Díaz Mauricio , Bacci Michael , Bottani Simona , El-Rifai Omar , Fontanella Sabrina , Gori Pietro , Guillon Jérémy , Guyot Alexis , Hassanaly Ravi , Jacquemont Thomas , Lu Pascal , Marcoux Arnaud , Moreau Tristan , Samper-González Jorge , Teichmann Marc , Thibeau-Sutre Elina , Vaillant Ghislain , Wen Junhao , Wild Adam , Habert Marie-Odile , Durrleman Stanley , Colliot Olivier TITLE=Clinica: An Open-Source Software Platform for Reproducible Clinical Neuroscience Studies JOURNAL=Frontiers in Neuroinformatics VOLUME=15 YEAR=2021 URL=https://www.frontiersin.org/journals/neuroinformatics/articles/10.3389/fninf.2021.689675 DOI=10.3389/fninf.2021.689675 ISSN=1662-5196 ABSTRACT=

We present Clinica (www.clinica.run), an open-source software platform designed to make clinical neuroscience studies easier and more reproducible. Clinica aims for researchers to (i) spend less time on data management and processing, (ii) perform reproducible evaluations of their methods, and (iii) easily share data and results within their institution and with external collaborators. The core of Clinica is a set of automatic pipelines for processing and analysis of multimodal neuroimaging data (currently, T1-weighted MRI, diffusion MRI, and PET data), as well as tools for statistics, machine learning, and deep learning. It relies on the brain imaging data structure (BIDS) for the organization of raw neuroimaging datasets and on established tools written by the community to build its pipelines. It also provides converters of public neuroimaging datasets to BIDS (currently ADNI, AIBL, OASIS, and NIFD). Processed data include image-valued scalar fields (e.g., tissue probability maps), meshes, surface-based scalar fields (e.g., cortical thickness maps), or scalar outputs (e.g., regional averages). These data follow the ClinicA Processed Structure (CAPS) format which shares the same philosophy as BIDS. Consistent organization of raw and processed neuroimaging files facilitates the execution of single pipelines and of sequences of pipelines, as well as the integration of processed data into statistics or machine learning frameworks. The target audience of Clinica is neuroscientists or clinicians conducting clinical neuroscience studies involving multimodal imaging, and researchers developing advanced machine learning algorithms applied to neuroimaging data.