Training Subset — Unannotated (Original 3D LSM Images)
The training set with no annotation for self-supervised learning are the original 3D LSM images where the unannotated patches in Task 1 come from. This set contains a total of 66 large 3D LSM images.
Isolated Structures (30 images, each exceeding 4×1010 voxels, amounting to over 44,000 patches)
| Structure Type | Images |
|---|---|
| c-Fos+ cells [1] | 18 |
| Cell nuclei [2] | 4 |
| Amyloid-beta plaques [3] | 4 |
| Chondrocytes [4] | 1 |
| Chondrogenic cells [4] | 1 |
| Dopaminergic neurons [5] | 1 |
| Astrocytes [5] | 1 |
Contiguous Structures (36 images, each exceeding 3×1010 voxels, amounting to over 40,000 patches)
| Structure Type | Images |
|---|---|
| Blood vessels [6] | 9 |
| Arteries [7] | 4 |
| Sympathetic nerves [7] | 4 |
| Peripheral nerves (PGP9.5) [4, 5, 7, 8] | 5 |
| Lymphatic vessels [7] | 4 |
| Cranial nerves [4, 5] | 2 |
| Axonal markers [9] | 8 |
Annotated Training, Preliminary Test & Final Test Sets
The annotated cases in the training, preliminary test, and final test sets are the same as in Task 1. Please refer to the Dataset for Task 1 page for full details.
References
[1] D. Kaltenecker, R. Al-Maskari, M. Negwer, et al. Virtual reality empowered deep learning analysis of brain activity. Nature Methods 21: 1306–1315, 2024 April.
[2] S. Zhao, M.I. Todorov, R. Cai, et al. Cellular and molecular probing of intact human organs. Cell 180(4): 796-812, 2020 Feb.
[3] H.S. Bhatia, A. Brunner, F. Öztürk, et al. Spatial proteomics in three-dimensional intact specimens. Cell 185(26): 5040-5058, 2022 Dec.
[4] R. Blain, G. Couly, E. Shotar, et al. A tridimensional atlas of the developing human head. Cell 186(26): 5910-5924, 2023 Dec.
[5] https://mab3d-atlas.com/validated-antibody-database
[6] M.I. Todorov, J.C. Paetzold, O. Schoppe, et al. Machine learning analysis of whole mouse brain vasculature. Nature Methods 17: 442-449, 2020 Mar.
[7] H. Mai, J. Luo, L. Hoeher, et al. Whole-body cellular mapping in mouse using standard IgG antibodies. Nature Biotechnology 42: 617–627, 2023 July.
[8] R. Cai, C. Pan, A. Ghasemigharagoz, et al. Panoptic imaging of transparent mice reveals whole-body neuronal projections and skull-meninges connections. Nature Neuroscience 22: 317-327, 2019 Dec.
[9] E. Özen, et al. Multicolor High Resolution SCAPE microscopy for Understanding Neural Connectivity. Optics and the Brain, Optica Publishing Group, 2025.
[1] D. Kaltenecker, R. Al-Maskari, M. Negwer, et al. Virtual reality empowered deep learning analysis of brain activity. Nature Methods 21: 1306–1315, 2024 April.
[2] S. Zhao, M.I. Todorov, R. Cai, et al. Cellular and molecular probing of intact human organs. Cell 180(4): 796-812, 2020 Feb.
[3] H.S. Bhatia, A. Brunner, F. Öztürk, et al. Spatial proteomics in three-dimensional intact specimens. Cell 185(26): 5040-5058, 2022 Dec.
[4] R. Blain, G. Couly, E. Shotar, et al. A tridimensional atlas of the developing human head. Cell 186(26): 5910-5924, 2023 Dec.
[5] https://mab3d-atlas.com/validated-antibody-database
[6] M.I. Todorov, J.C. Paetzold, O. Schoppe, et al. Machine learning analysis of whole mouse brain vasculature. Nature Methods 17: 442-449, 2020 Mar.
[7] H. Mai, J. Luo, L. Hoeher, et al. Whole-body cellular mapping in mouse using standard IgG antibodies. Nature Biotechnology 42: 617–627, 2023 July.
[8] R. Cai, C. Pan, A. Ghasemigharagoz, et al. Panoptic imaging of transparent mice reveals whole-body neuronal projections and skull-meninges connections. Nature Neuroscience 22: 317-327, 2019 Dec.
[9] E. Özen, et al. Multicolor High Resolution SCAPE microscopy for Understanding Neural Connectivity. Optics and the Brain, Optica Publishing Group, 2025.