ArticlePloS one2015
Evaluation of Cross-Protocol Stability of a Fully Automated Brain Multi-Atlas Parcellation Tool.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Anatomical and Functional Characterization in Children With Unilateral Cerebral Palsy: An Atlas-Based Analysis.Neurorehabilitation and neural repair · 2020Trial
- Multimodal Brain MRI of Deep Gray Matter Changes Associated With Inflammatory Bowel Disease.Inflammatory bowel diseases · 2023Article
- Longitudinal imaging highlights preferential basal ganglia circuit atrophy in Huntington's disease.Brain communications · 2023Article
- Brain atrophy in middle age using magnetic resonance imaging scans from Japan's health screening programme.Brain communications · 2022Article
- Systematic volumetric analysis predicts response to CSF drainage and outcome to shunt surgery in idiopathic normal pressure hydrocephalus.European radiology · 2021Article
- Gray matter alteration in heroin-dependent men: An atlas-based magnetic resonance imaging study.Psychiatry research. Neuroimaging · 2020Article
- Using deep Siamese neural networks for detection of brain asymmetries associated with Alzheimer's Disease and Mild Cognitive Impairment.Magnetic resonance imaging · 2019Article
- Test-retest reproducibility of a multi-atlas automated segmentation tool on multimodality brain MRI.Brain and behavior · 2019Article
- A Multi-Atlas Label Fusion Tool for Neonatal Brain MRI Parcellation and Quantification.Journal of neuroimaging : official journal of the American Society of Neuroimaging · 2019Article
- Article
- Regional subcortical shape analysis in premanifest Huntington's disease.Human brain mapping · 2019Article
- Automated Generation of Radiologic Descriptions on Brain Volume Changes From T1-Weighted MR Images: Initial Assessment of Feasibility.Frontiers in neurology · 2019Article
- Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRI-Application in Premanifest Huntington's Disease.Journal of visualized experiments : JoVE · 2018Article
- A Fully-Automated Subcortical and Ventricular Shape Generation Pipeline Preserving Smoothness and Anatomical Topology.Frontiers in neuroscience · 2018Article
- Multi-Granularity Whole-Brain Segmentation Based Functional Network Analysis Using Resting-State fMRI.Frontiers in neuroscience · 2018Article
- Mapping the order and pattern of brain structural MRI changes using change-point analysis in premanifest Huntington's disease.Human brain mapping · 2017Article
- Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2017Review
- Brain MRI Pattern Recognition Translated to Clinical Scenarios.Frontiers in neuroscience · 2017Article
- Shape and diffusion tensor imaging based integrative analysis of the hippocampus and the amygdala in Alzheimer's disease.Magnetic resonance imaging · 2016Article
- Resource atlases for multi-atlas brain segmentations with multiple ontology levels based on T1-weighted MRI.NeuroImage · 2016Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Brain parcellation tools based on multiple-atlas algorithms have recently emerged as a promising method with which to accurately define brain structures. When dealing with data from various sources, it is crucial that these tools are robust for many different imaging protocols. In this study, we tested the robustness of a multiple-atlas, likelihood fusion algorithm using Alzheimer's Disease Neuroimaging Initiative (ADNI) data with six different protocols, comprising three manufacturers and two magnetic field strengths. The entire brain was parceled into five different levels of granularity. In each level, which defines a set of brain structures, ranging from eight to 286 regions, we evaluated the variability of brain volumes related to the protocol, age, and diagnosis (healthy or Alzheimer's disease). Our results indicated that, with proper pre-processing steps, the impact of different protocols is minor compared to biological effects, such as age and pathology. A precise knowledge of the sources of data variation enables sufficient statistical power and ensures the reliability of an anatomical analysis when using this automated brain parcellation tool on datasets from various imaging protocols, such as clinical databases.
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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.