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Recent Advances in Hypothalamic Segmentation for Neuroimaging: A Comprehensive Review
1From the Department of Radiology, The First Hospital of Jilin University, Changchun, Jilin, China (J.Z.H., Z.P.C., X.C.P., D.T.); and the Reproductive Medicine Center, Prenatal Diagnosis Center, First Hospital of Jilin University, Changchun, China (C.H.).
AJNR. American Journal of Neuroradiology
|December 18, 2025
Summary
This review summarizes methods for segmenting the hypothalamus, a key brain region. Standardized approaches are needed for accurate analysis of its complex structure and function, especially in children.
Area of Science:
- Neuroscience
- Medical Imaging
- Computational Biology
Background:
- The hypothalamus regulates vital physiological processes like energy balance and circadian rhythms.
- Its complex structure with distinct subnuclei necessitates precise segmentation for functional studies.
- Current research faces challenges due to a lack of unified segmentation protocols and pediatric data.
Purpose of the Study:
- To systematically review current hypothalamic segmentation methods.
- To discuss their applications in physiological and clinical research.
- To identify challenges and propose future directions for improved segmentation.
Main Methods:
- Categorization of segmentation approaches into anatomy-based manual and deep learning-based automated methods.
- Review of existing literature on hypothalamic segmentation techniques and their validation.
- Analysis of applications in physiological and clinical research contexts.
Main Results:
- Two primary segmentation types exist: manual (expert-driven, for validation) and automated (deep learning, for large-scale studies).
- Manual segmentation offers gold-standard accuracy for key subregions.
- Automated segmentation provides efficiency for exploring hypothalamic heterogeneity.
Conclusions:
- Standardized segmentation workflows are crucial for comparability and reproducibility.
- Addressing methodological gaps in pediatric hypothalamic segmentation is essential.
- Future efforts should focus on reducing bias and improving accuracy for comprehensive understanding.
