Your browser doesn't support javascript.
loading
A collection of 157 individual neuromelanin-sensitive images accompanied by non-linear neuromelanin-sensitive atlas and a probabilistic locus coeruleus atlas.
Lee, Tae-Ho; Kim, Sun Hyung; Neal, Joshua; Katz, Benjamin; Kim, Il Hwan.
Affiliation
  • Lee TH; Department of Psychology, Virginia Tech, USA.
  • Kim SH; School of Neuroscience, Virginia Tech, USA.
  • Neal J; Department of Psychiatry, University of North Carolina, Chapel Hill, USA.
  • Katz B; Department of Psychology, Virginia Tech, USA.
  • Kim IH; Department of Human Development and Family Science, Virginia Tech, USA.
Data Brief ; 53: 110140, 2024 Apr.
Article in En | MEDLINE | ID: mdl-38357452
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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Diagnostic_studies Language: En Journal: Data Brief Year: 2024 Document type: Article Affiliation country: United States Country of publication: Netherlands

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Diagnostic_studies Language: En Journal: Data Brief Year: 2024 Document type: Article Affiliation country: United States Country of publication: Netherlands