@article{bibcite_6431,
  keywords = {Biomedical Engineering, Biophysical models},
  author = {Adri{\`a} Casamitjana and Matteo Mancini and Eleanor Robinson and Lo{\"\i}c Peter and Roberto Annunziata and Juri Althonayan and Shauna Crampsie and Emily Blackburn and Benjamin Billot and Alessia Atzeni and Oula Puonti and Ya{\"e}l Balbastre and Peter Schmidt and James Hughes and Jean C. Augustinack and Brian L. Edlow and Lilla Z{\"o}llei and David L. Thomas and Dorit Kliemann and Martina Bocchetta and Catherine Strand and Janice L. Holton and Zane Jaunmuktane and Juan Eugenio Iglesias},
  title = {A probabilistic histological atlas of the human brain for MRI segmentation},
  abstract = {In human neuroimaging, brain atlases are essential for segmenting regions of interest (ROIs) and comparing subjects in a common coordinate frame. State-of-the-art atlases derived from histology1{\textendash}3 provide exquisite three-dimensional cytoarchitectural maps but lack probabilistic labels throughout the whole brain: that is, the likelihood of each location belonging to a given ROI. Here we present NextBrain, a probabilistic histological atlas of the whole human brain. We developed artificial intelligence-enabled methods to align roughly 10,000 histological sections from five whole brain hemispheres into three-dimensional volumes and to produce delineations for 333 ROIs on these sections. We also created a companion Bayesian tool for automatic segmentation of these ROIs in magnetic resonance imaging (MRI) scans. We showcase two applications of the atlas: segmentation of ultra-high-resolution ex vivo MRI and volumetric analysis of Alzheimer{\textquoteright}s disease using in vivo MRI. We publicly release raw and aligned data, an online visualization tool, the atlas, the segmentation tool, and ground truth delineations for a high-resolution ex vivo hemisphere used in validation. By enabling researchers worldwide to automatically analyse brain MRIs at a higher level of granularity, NextBrain holds promise to increase the specificity of findings and accelerate our quest to understand the human brain in health and disease.},
  year = {2025},
  journal = {Nature},
  pages = {1-8},
  month = {2025-11-05},
  issn = {1476-4687},
  url = {https://www.nature.com/articles/s41586-025-09708-2},
  doi = {10.1038/s41586-025-09708-2},
  language = {en},
}