ArticleFrontiers in neuroinformatics2021
Clinica: An Open-Source Software Platform for Reproducible Clinical Neuroscience Studies.
Article in Frontiers in neuroinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.
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Who cites it
41 citing papers in PubMed, 1 synthesis or guideline pooled it, 125 citations in OpenAlex.
- Reproducible Evaluation of Diffusion MRI Features for Automatic Classification of Patients with Alzheimer's Disease.Neuroinformatics · 2021Pooled it
- A false discovery rate control method using a fully connected hidden Markov random field for neuroimaging data.Medical image analysis · 2026Article
- Unsupervised anomaly detection with deep generative models: an experimental analysis of model variability and mitigation strategies.Journal of medical imaging (Bellingham, Wash.) · 2026Article
- Clinical pathways matter for multimodal deep learning in early Alzheimer's disease detection.Scientific reports · 2026Article
- Composite grey matter fingerprints for genetic frontotemporal dementia.Journal of neurology, neurosurgery, and psychiatry · 2026Article
- Decision Strategies in AI-Based Ensemble Models in Opportunistic Alzheimer's Detection from Structural MRI.Journal of imaging informatics in medicine · 2026Article
- Applying machine-learning and deep-learning to predict depression from brain MRI and identify depression-related brain biology.Translational psychiatry · 2026Article
- Synergistic and redundant information dynamics are modulated by Alzheimer's disease and cognitive impairment.bioRxiv : the preprint server for biology · 2026Article
- Prediction of brain age using structural magnetic resonance imaging: a comparison of clinical utility of publicly available software packages.EBioMedicine · 2026Article
- Estimation of head motion in structural MRI and its impact on cortical morphometry.Frontiers in neuroscience · 2026Article
- Vision and convolutional transformers for Alzheimer's disease diagnosis: a systematic review of architectures, multimodal fusion and critical gaps.Brain informatics · 2025Review
- Pennsieve: A Collaborative Platform for Translational Neuroscience and Beyond.Scientific data · 2025Article
- Benchmarking 3D generative autoencoders for pseudo-healthy reconstruction of brainJournal of medical imaging (Bellingham, Wash.) · 2025Article
- A multi-modal graph-based framework for Alzheimer's disease detection.Scientific reports · 2025Article
- Structural and functional connectivity in tau mutation carriers: from presymptomatic to symptomatic frontotemporal dementia.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Reevaluating the Role of Education in Cognitive Decline and Brain Aging: Insights from Large-Scale Longitudinal Cohorts across 33 Countries.medRxiv : the preprint server for health sciences · 2025Article
- Automatic rating of incomplete hippocampal inversions evaluated across multiple cohorts.ArXiv · 2025Article
- Open-source platforms to investigate analytical flexibility in neuroimaging.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Contrastive self-supervised learning for neurodegenerative disorder classification.Frontiers in neuroinformatics · 2025Article
- The interplay of age, gender and amyloid on brain and cognition in mid-life and older adults.Scientific reports · 2024Article
Corrections and comments
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Authors and funding
24 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.