A probabilistic histological atlas of the human brain for MRI segmentation.
Authors
Affiliations (18)
Affiliations (18)
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK.
- Research Institute of Computer Vision and Robotics, University of Girona, Girona, Spain.
- Enrico Fermi Research Center, Rome, Italy.
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, UK.
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark.
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
- Advanced Research Computing Centre, University College London, London, UK.
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK.
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK.
- Department of Psychological and Brain Sciences, The University of Iowa, Iowa City, IA, USA.
- Department of Psychiatry, The University of Iowa, Iowa City, IA, USA.
- Centre for Cognitive and Clinical Neuroscience, Division of Psychology, Department of Life Sciences, College of Health, Medicine and Life Sciences, Brunel University London, London, UK.
- Queen Square Brain Bank for Neurological Disorders, Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK.
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK. [email protected].
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA. [email protected].
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA. [email protected].
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 histology<sup>1-3</sup> 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.