3D light-sheet microscopy data for SELMA3D 2026 challenge - contiguous structures - training subset with annotations

ABSTRACT: This dataset is the training set with annotations of contiguous structures for SELMA3D 2026 challenge. The SELMA3D 2026 challenge focuses on self-supervised learning for 3D light-sheet microscopy (LSM) image segmentation. Its objective is to encourage the development of generalizable models capable of serving multiple 3D LSM image segmentation tasks. This dataset contains 3D image patches of different contiguous structures including blood vessels, nerves and axons. Each patch includes corresponding pixel-wise annotations for the structures.

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PROVIDER: S-BIAD2106 | bioimages |

REPOSITORIES: bioimages