Atlas learning in fetal brain development.

Area of Science:

• Neuroimaging
• Developmental Neuroscience
• Medical Imaging Analysis

Background:

• Magnetic resonance imaging (MRI) is a vital noninvasive tool for studying fetal brain development, surpassing ultrasound in diagnosing high-risk pregnancies.
• Atlases are essential for summarizing population-based MRI findings and establishing correspondences across cohorts.
• Understanding human brain development requires robust reference systems and models that capture population characteristics.

Purpose of the Study:

• To review the evolution of atlas-building methods for modeling human brain development.
• To discuss the relevance, limitations, and benefits of various atlas approaches.
• To highlight methods that model population variability over time, including disease progression and development.

Main Methods:

• Review of historical atlas methods (e.g., Talairach, Montreal Neurological Institute space).
• Exploration of methods for heterogeneous populations and minimal annotation generalization.
• Focus on time-dependent variability modeling for development and disease progression.

Main Results:

• Atlases serve as crucial models capturing population characteristics and enabling cross-cohort correspondences.
• Advanced methods increasingly accommodate population heterogeneity and generalize with less annotation.
• Time-dependent modeling approaches are key for understanding dynamic processes like brain development and disease progression.

Conclusions:

• Atlas-building methods have evolved significantly, offering powerful tools for developmental neuroscience.
• Modeling population variability, especially over time, is critical for accurate insights into brain development and disease.
• Future research should focus on refining these methods and their application to complex developmental trajectories.