TY - JOUR AU - Routier, Alexandre AU - Burgos, Ninon AU - Díaz, Mauricio AU - Bacci, Michael AU - Bottani, Simona AU - El-Rifai, Omar AU - Fontanella, Sabrina AU - Gori, Pietro AU - Guillon, Jérémy AU - Guyot, Alexis AU - Hassanaly, Ravi AU - Jacquemont, Thomas AU - Lu, Pascal AU - Marcoux, Arnaud AU - Moreau, Tristan AU - Samper-González, Jorge AU - Teichmann, Marc AU - Thibeau-Sutre, Elina AU - Vaillant, Ghislain AU - Wen, Junhao AU - Wild, Adam AU - Habert, Marie-Odile AU - Durrleman, Stanley AU - Colliot, Olivier PY - 2021 M3 - Original Research TI - Clinica: An Open-Source Software Platform for Reproducible Clinical Neuroscience Studies JO - Frontiers in Neuroinformatics UR - https://www.frontiersin.org/articles/10.3389/fninf.2021.689675 VL - 15 SN - 1662-5196 N2 - 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. ER -