# A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology

arXiv: https://arxiv.org/abs/1806.08634 · HTML: https://mlsanity.com/paper/1806.08634/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Jun 2018.

## Built on by (most cited first, 10 of 10)

- [SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining](https://mlsanity.com/paper/2107.09559/) (2021)
- [Robust machine learning segmentation for large-scale analysis of heterogeneous clinical brain MRI datasets](https://mlsanity.com/paper/2209.02032/) (2022)
- [Robust joint registration of multiple stains and MRI for multimodal 3D histology reconstruction: Application to the Allen human brain atlas](https://mlsanity.com/paper/2104.14873/) (2021)
- [H-SynEx: Using synthetic images and ultra-high resolution ex vivo MRI for hypothalamus subregion segmentation](https://mlsanity.com/paper/2401.17104/) (2024)
- [Comprehensive segmentation of deep grey nuclei from structural MRI data](https://mlsanity.com/paper/2503.21955/) (2025)
- [Domain-agnostic segmentation of thalamic nuclei from joint structural and diffusion MRI](https://mlsanity.com/paper/2305.03413/) (2023)
- [DeepThalamus: A novel deep learning method for automatic segmentation of brain thalamic nuclei from multimodal ultra-high resolution MRI](https://mlsanity.com/paper/2401.07751/) (2024)
- [Surface-based parcellation and vertex-wise analysis of ultra high-resolution ex vivo 7 tesla MRI in Alzheimer's disease and related dementias](https://mlsanity.com/paper/2403.19497/) (2024)
- [High-resolution segmentations of the hypothalamus and its subregions for training of segmentation models](https://mlsanity.com/paper/2406.19492/) (2024)
- [Segmenting Thalamic Nuclei: T1 Maps Provide a Reliable and Efficient Solution](https://mlsanity.com/paper/2508.12508/) (2025)

## Abstract (arXiv)

The human thalamus is a brain structure that comprises numerous, highly specific nuclei. Since these nuclei are known to have different functions and to be connected to different areas of the cerebral cortex, it is of great interest for the neuroimaging community to study their volume, shape and connectivity in vivo with MRI. In this study, we present a probabilistic atlas of the thalamic nuclei built using ex vivo brain MRI scans and histological data, as well as the application of the atlas to in vivo MRI segmentation. The atlas was built using manual delineation of 26 thalamic nuclei on the serial histology of 12 whole thalami from six autopsy samples, combined with manual segmentations of the whole thalamus and surrounding structures (caudate, putamen, hippocampus, etc.) made on in vivo brain MR data from 39 subjects. The 3D structure of the histological data and corresponding manual segmentations was recovered using the ex vivo MRI as reference frame, and stacks of blockface photographs acquired during the sectioning as intermediate target. The atlas, which was encoded as an adaptive tetrahedral mesh, shows a good agreement with with previous histological studies of the thalamus in terms of volumes of representative nuclei. When applied to segmentation of in vivo scans using Bayesian inference, the atlas shows excellent test-retest reliability, robustness to changes in input MRI contrast, and ability to detect differential thalamic effects in subjects with Alzheimer's disease. The probabilistic atlas and companion segmentation tool are publicly available as part of the neuroimaging package FreeSurfer.