ArticleNeuroImage2021
Labeling lateral prefrontal sulci using spherical data augmentation and context-aware training.
Article in NeuroImage, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 41 citations in OpenAlex.
- Anchoring Functional Connectivity to Individual Sulcal Morphology Yields Insights in a Pediatric Study of Reasoning.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Leveraging Input-Level Feature Deformation With Guided-Attention for Sulcal Labeling.IEEE transactions on medical imaging · 2025Article
- Anchoring functional connectivity to individual sulcal morphology yields insights in a pediatric study of reasoning.bioRxiv : the preprint server for biology · 2025Article
- Unique longitudinal contributions of sulcal interruptions to reading acquisition in children.bioRxiv : the preprint server for biology · 2024Article
- Morphological patterns and spatial probability maps of the inferior frontal sulcus in the human brain.Human brain mapping · 2024Article
- Updating the sulcal landscape of the human lateral parieto-occipital junction provides anatomical, functional, and cognitive insights.bioRxiv : the preprint server for biology · 2024Article
- Defining Overlooked Structures Reveals New Associations between the Cortex and Cognition in Aging and Alzheimer's Disease.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Neuroanatomical and Functional Dissociations between Variably Present Anterior Lateral Prefrontal Sulci.Journal of cognitive neuroscience · 2023Article
- Neuroanatomical and functional dissociations between variably present anterior lateral prefrontal sulci.bioRxiv : the preprint server for biology · 2023Article
- Sulcal depth in prefrontal cortex: a novel predictor of working memory performance.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- Functionally and structurally distinct fusiform face area(s) in over 1000 participants.NeuroImage · 2023Article
- Article
- Uncovering a tripartite landmark in posterior cingulate cortex.Science advances · 2022Article
- TopoFit: Rapid Reconstruction of Topologically-Correct Cortical Surfaces.Proceedings of machine learning research · 2022Article
- Cognitive insights from tertiary sulci in prefrontal cortex.Nature communications · 2021Article
- Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future.Sensors (Basel, Switzerland) · 2021Review
- Overlooked Tertiary Sulci Serve as a Meso-Scale Link between Microstructural and Functional Properties of Human Lateral Prefrontal Cortex.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Article
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Authors and funding
10 authors at 4 institutions in 1 country.
Funding
Abstract
The inference of cortical sulcal labels often focuses on deep (primary and secondary) sulcal regions, whereas shallow (tertiary) sulcal regions are largely overlooked in the literature due to the scarcity of manual/well-defined annotations and their large neuroanatomical variability. In this paper, we present an automated framework for regional labeling of both primary/secondary and tertiary sulci of the dorsal portion of lateral prefrontal cortex (LPFC) using spherical convolutional neural networks. We propose two core components that enhance the inference of sulcal labels to overcome such large neuroanatomical variability: (1) surface data augmentation and (2) context-aware training. (1) To take into account neuroanatomical variability, we synthesize training data from the proposed feature space that embeds intermediate deformation trajectories of spherical data in a rigid to non-rigid fashion, which bridges an augmentation gap in conventional rotation data augmentation. (2) Moreover, we design a two-stage training process to improve labeling accuracy of tertiary sulci by informing the biological associations in neuroanatomy: inference of primary/secondary sulci and then their spatial likelihood to guide the definition of tertiary sulci. In the experiments, we evaluate our method on 13 deep and shallow sulci of human LPFC in two independent data sets with different age ranges: pediatric (N=60) and adult (N=36) cohorts. We compare the proposed method with a conventional multi-atlas approach and spherical convolutional neural networks without/with rotation data augmentation. In both cohorts, the proposed data augmentation improves labeling accuracy of deep and shallow sulci over the baselines, and the proposed context-aware training offers further improvement in the labeling of shallow sulci over the proposed data augmentation. We share our tools with the field and discuss applications of our results for understanding neuroanatomical-functional organization of LPFC and the rest of cortex (https://github.com/ilwoolyu/SphericalLabeling).
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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.