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Individual brain parcellation: Review of methods, validations and applications

arXiv 2407.00984 ↗First posted 1 Jul 2024q-bio.NC cs.AIcited by 2

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Abstract (arXiv)

Individual brains vary greatly in morphology, connectivity and organization. The applicability of group-level parcellations is limited by the rapid development of precision medicine today because they do not take into account the variation of parcels at the individual level. Accurate mapping of brain functional regions at the individual level is pivotal for a comprehensive understanding of the variations in brain function and behaviors, early and precise identification of brain abnormalities, as well as personalized treatments for neuropsychiatric disorders. With the development of neuroimaging and machine learning techniques, studies on individual brain parcellation are booming. In this paper, we offer an overview of recent advances in the methodologies of individual brain parcellation, including optimization- and learning-based methods. Comprehensive evaluation metrics to validate individual brain mapping have been introduced. We also review the studies of how individual brain mapping promotes neuroscience research and clinical medicine. Finally, we summarize the major challenges and important future directions of individualized brain parcellation. Collectively, we intend to offer a thorough overview of individual brain parcellation methods, validations, and applications, along with highlighting the current challenges that call for an urgent demand for integrated platforms that integrate datasets, methods, and validations.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 2 of its 107 references that are in the map. First posted on arXiv 1 Jul 2024.

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2 of 107 references.

References · 2

  1. 2023SwiFT: Swin 4D fMRI Transformercited by 36
  2. 2018Brain Age Prediction Based on Resting-State Functional Connectivity Patterns Using Convolutional Neural Networkscited by 7

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