  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.
