ArticleFrontiers in neuroinformatics2019
FuNP (Fusion of Neuroimaging Preprocessing) Pipelines: A Fully Automated Preprocessing Software for Functional Magnetic Resonance Imaging.
Article in Frontiers in neuroinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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29 citing papers in PubMed.
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- Quality Assurance Strategies for Brain State Characterization by MEMRI.bioRxiv : the preprint server for biology · 2026Article
- Alterations in the functional MRI-based temporal brain organisation in individuals with obesity.Diabetes, obesity & metabolism · 2025Article
- Structural connectome manifold changes related to body mass index and their associations with eating psychopathology.NeuroImage. Clinical · 2025Article
- Employing Informatics Strategies in Alzheimer's Disease Research: A Review from Genetics, Multiomics, and Biomarkers to Clinical Outcomes.Annual review of biomedical data science · 2024Review
- Shifts in structural connectome organization in the limbic and sensory systems of patients with episodic migraine.The journal of headache and pain · 2024Article
- fMRI-based Alzheimer's disease detection via functional connectivity analysis: a systematic review.PeerJ. Computer science · 2024Article
- Identifying subgroups of eating behavior traits unrelated to obesity using functional connectivity and feature representation learning.Human brain mapping · 2024Article
- Whole-brain functional gradients reveal cortical and subcortical alterations in patients with episodic migraine.Human brain mapping · 2023Article
- Autism Spectrum Disorder Detection by Hybrid Convolutional Recurrent Neural Networks from Structural and Resting State Functional MRI Images.Autism research and treatment · 2023Article
- QuNex-An integrative platform for reproducible neuroimaging analytics.Frontiers in neuroinformatics · 2023Article
- The evolution of Big Data in neuroscience and neurology.Journal of big data · 2023Article
- Normalization Strategies in Multi-Center Radiomics Abdominal MRI: Systematic Review and Meta-Analyses.IEEE open journal of engineering in medicine and biology · 2023Article
- Automatic theranostics for long-term neurorehabilitation after stroke.Frontiers in aging neuroscience · 2023Article
- DAD-Net: Classification of Alzheimer's Disease Using ADASYN Oversampling Technique and Optimized Neural Network.Molecules (Basel, Switzerland) · 2022Article
- Cerebrovascular reactivity and deep white matter hyperintensities in migraine: A prospective COJournal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2022Article
- Adolescent development of multiscale structural wiring and functional interactions in the human connectome.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- An integrated cluster-wise significance measure for fMRI analysis.Human brain mapping · 2022Article
- Disrupted stepwise functional brain organization in overweight individuals.Communications biology · 2022Article
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3 authors.
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Abstract
The preprocessing of functional magnetic resonance imaging (fMRI) data is necessary to remove unwanted artifacts and transform the data into a standard format. There are several neuroimaging data processing tools that are widely used, such as SPM, AFNI, FSL, FreeSurfer, Workbench, and fMRIPrep. Different data preprocessing pipelines yield differing results, which might reduce the reproducibility of neuroimaging studies. Here, we developed a preprocessing pipeline for T1-weighted structural MRI and fMRI data by combining components of well-known software packages to fully incorporate recent developments in MRI preprocessing into a single coherent software package. The developed software, called FuNP (Fusion of Neuroimaging Preprocessing) pipelines, is fully automatic and provides both volume- and surface-based preprocessing pipelines with a user-friendly graphical interface. The reliability of the software was assessed by comparing resting-state networks (RSNs) obtained using FuNP with pre-defined RSNs using open research 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.