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http://bura.brunel.ac.uk/handle/2438/32379| Title: | A probabilistic histological atlas of the human brain for MRI segmentation |
| Authors: | Casamitjana, A Mancini, M Robinson, E Peter, L Annunziata, R Althonayan, J Crampsie, S Blackburn, E Billot, B Atzeni, A Puonti, O Balbastre, Y Schmidt, P Hughes, J Augustinack, JC Edlow, BL Zöllei, L Thomas, DL Kliemann, D Bocchetta, M Strand, C Holton, JL Jaunmuktane, Z Iglesias, JE |
| Keywords: | biomedical engineering;biophysical models |
| Issue Date: | 5-Nov-2025 |
| Publisher: | Springer Nature |
| Citation: | Casamitjana, A. et al. (2025) 'A probabilistic histological atlas of the human brain for MRI segmentation', Nature, 0 (ahead of print), pp. 1 - 29. doi: 10.1038/s41586-025-09708-2. |
| 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 histology1,2,3 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’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. |
| Description: | Data availability:
The raw data used in this Article (MRI, histology, segmentations and so on) can be downloaded from https://doi.org/10.5522/04/24243835. An online tool to interactively explore the 3D reconstructed data can be found at https://github-pages.ucl.ac.uk/NextBrain. This website also includes links to videos, publications, code and other resources. The segmentation of the ex vivo scan can be found at https://openneuro.org/datasets/ds005422/versions/1.0.1. The databases used in the aging study are freely accessible online: OpenBHB (https://baobablab.github.io/bhb/) and aHCP (https://www.humanconnectome.org/study/hcp-lifespan-aging). The ADNI dataset used in the Alzheimer’s disease study is freely accessible with registration at https://adni.loni.usc.edu/data-samples/adni-data/. The atlases used in the Supplementary Information for comparison can be found online: Mai-Paixinos (https://www.thehumanbrain.info/brain/sections.php) and Allen (https://atlas.brain-map.org/). Code availability: The code used in this Article for 3D histology reconstruction can be downloaded from https://github.com/acasamitjana/ERC_reconstruction and used and distributed freely. The segmentation tool is provided as Python code and is integrated in our neuroimaging toolkit ‘FreeSurfer’: https://surfer.nmr.mgh.harvard.edu/fswiki/HistoAtlasSegmentation. The source code is available on GitHub: https://github.com/freesurfer/freesurfer/tree/dev/mri_histo_util . Extended data figures and tables are available online at: https://www.nature.com/articles/s41586-025-09708-2#Sec33 . Supplementary information is available online at: https://www.nature.com/articles/s41586-025-09708-2#Sec34 . |
| URI: | https://bura.brunel.ac.uk/handle/2438/32379 |
| DOI: | https://doi.org/10.1038/s41586-025-09708-2 |
| ISSN: | 0028-0836 |
| Other Identifiers: | ORCiD: Shauna Crampsie https://orcid.org/0000-0002-4399-5218 ORCiD: Oula Puonti https://orcid.org/0000-0003-3186-244X ORCiD: James Hughes https://orcid.org/0000-0002-3022-3104 ORCiD: Brian L. Edlow https://orcid.org/0000-0001-7235-8456 ORCiD: Lilla Zöllei https://orcid.org/0000-0002-6447-9626 ORCiD: David L. Thomas https://orcid.org/0000-0003-1491-1641 ORCiD: Martina Bocchetta https://orcid.org/0000-0003-1814-5024 ORCiD: Zane Jaunmuktane https://orcid.org/0000-0001-7738-8881 ORCiD: Juan Eugenio Iglesias https://orcid.org/0000-0001-7569-173X |
| Appears in Collections: | Dept of Life Sciences Research Papers |
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