Artificial intelligence (AI) is rapidly transforming health care, and its applications in epilepsy
have increased exponentially over the past decade. Integration of AI into epilepsy …

In the chapters in Part I of this textbook the author introduces the fundamental ideas of
artificial intelligence and computational intelligence. In Part II he explains key AI methods …

Abstract 3D brain atlases are key resources to understand the brain's spatial organization
and promote interoperability across different studies. However, unlike the adult mouse brain …

Volumetric brain atlases are increasingly used to integrate and analyze diverse
experimental neuroscience data acquired from animal models, but until recently a publicly …

Objective. De-centralized data analysis becomes an increasingly preferred option in the
healthcare domain, as it alleviates the need for sharing primary patient data across …

Exposure to blast overpressure has been a pervasive feature of combat-related injuries.
Studies exploring the neurological correlates of repeated low-level blast exposure in career …

Background Fetal exposure to maternal mood dysregulation influences child cognitive and
emotional development, which may have long-lasting implications for mental health …

Deformable templates are essential to large-scale medical image registration, segmentation,
and population analysis. Current conventional and deep network-based methods for …

Deep Learning (DL) has the potential to optimize machine learning in both the scientific and
clinical communities. However, greater expertise is required to develop DL algorithms, and …

Brain extraction (aka skull stripping) is a fundamental step in the neuroimaging pipeline as it
can affect the accuracy of downstream preprocess such as image registration, tissue …