TY - JOUR
T1 - A probabilistic histological atlas of the human brain for MRI segmentation
AU - Casamitjana, Adrià
AU - Mancini, Matteo
AU - Robinson, Eleanor
AU - Peter, Loïc
AU - Annunziata, Roberto
AU - Althonayan, Juri
AU - Crampsie, Shauna
AU - Blackburn, Emily
AU - Billot, Benjamin
AU - Atzeni, Alessia
AU - Puonti, Oula
AU - Balbastre, Yaël
AU - Schmidt, Peter
AU - Hughes, James
AU - Augustinack, Jean C.
AU - Edlow, Brian L.
AU - Zöllei, Lilla
AU - Thomas, David L
AU - Kliemann, Dorit
AU - Bocchetta, Martina
AU - Strand, Catherine
AU - Holton, Janice L
AU - Jaunmuktane, Zane
AU - Iglesias, Juan Eugenio
PY - 2025/11/5
Y1 - 2025/11/5
N2 - 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 histology 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’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.
AB - 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 histology 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’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.
UR - http://www.scopus.com/inward/record.url?scp=105021026120&partnerID=8YFLogxK
U2 - 10.1038/s41586-025-09708-2
DO - 10.1038/s41586-025-09708-2
M3 - Journal article
C2 - 39282320
SN - 0028-0836
VL - 648
SP - 678
EP - 685
JO - Nature
JF - Nature
IS - 8094
ER -