bioimagesUnknownhttps://www.ebi.ac.uk/biostudies/studies/S-BIAD1197bioimagesSpecimenStudy ComponentorganisationBiosampleAssociationsImage acquisitionShan ZhaoJohannes C. PaetzoldHarsharan Singh BhatiaAli ErturkDoris KalteneckerYing ChenMihail Todorovfalse3D light-sheet microscopy data for SELMA3D 2024 challenge - Training subset with no annotations - whole brain imagesThis dataset is the training set containing whole-brain images without annotations for the SELMA3D challenge. The SELMA3D challenge focuses on self-supervised learning for 3D light-sheet microscopy image segmentation. Its objective is to encourage the development of self-supervised learning methods for general segmentation of various structures in 3D light-sheet microscopy images. The dataset contains 3D whole-brain microscopy image of different labeled biological structures, including blood vessels, c-Fos labeled brain cells involved in neural activity, cell nuclei, and Alzheimer's disease plaques. 2024-06-06T00:00:00Z2024-11-28T21:15:09.916Z2024-06-04T18:55:18.451ZS-BIAD1197