Abstract
The current dataset aims to support and enhance the research reliability of neuromelanin regions in the brainstem, such as locus coeruleus (LC), by offering raw neuromelanin-sensitive images. The dataset includes raw neuromelanin-sensitive images from 157 healthy individuals (8-64 years old). In addition, leveraging individual neuromelanin-sensitive images, a non-linear neuromelanin-sensitive atlas, generated through an iterative warping process, is included to tackle the common challenge of a limited field of view in neuromelanin-sensitive images. Finally, the dataset encompasses a probabilistic LC atlas generated through a majority voting approach with pre-existing multiple atlas-based segmentations. This process entails warping pre-existing atlases onto individual spaces and identifying voxels with a majority consensus of over 50 % across the atlases. This LC probabilistic atlas can minimize uncertainty variance associated with choosing a specific single atlas.