Multimodal image matching, which refers to identifying and then corresponding the same or
similar structure/content from two or more images that are of significant modalities or …

Deep learning technologies have dramatically reshaped the field of medical image
registration over the past decade. The initial developments, such as regression-based and U …

Imaging technologies are increasingly used to generate high-resolution reference maps of
brain structure and function. Comparing experimentally generated maps to these reference …

A comprehensive map of the structural connectome in the human brain has been a coveted
resource for understanding macroscopic brain networks. Here we report an expert-vetted …

Recent studies have suggested that the brain's structural and functional networks (ie,
connectomics) can be constructed by various imaging technologies (eg, EEG/MEG; …

Recent advances in magnetic resonance imaging methods, including data acquisition, pre-
processing and analysis, have benefited research on the contributions of subcortical brain …

Although amyloid imaging with PiB-PET ([C-11] Pittsburgh Compound-B positron emission
tomography), and now with F-18-labeled tracers, has produced remarkably consistent …

Image segmentation is one of the most important tasks in medical image analysis and is
often the first and the most critical step in many clinical applications. In brain MRI analysis …

Many neurological diseases and delineating pathological regions have been analyzed, and
the anatomical structure of the brain researched with the aid of magnetic resonance imaging …

Longitudinal image analysis has become increasingly important in clinical studies of normal
aging and neurodegenerative disorders. Furthermore, there is a growing appreciation of the …