3D nuclei instance segmentation dataset of fluorescence microscopy volumes of C. elegans

The dataset consists of 28 confocal microscopy volumes of C. elegans worms at the L1 stage and corresponding stacks of densely annotated nuclei instance segmentation masks. * 28 raw images and corresponding masks of average dimension (xyz) 1050 x 140 x 140 * Pixelsize (xyz): 0.116 x 0.116 x 0.122μm * Microscope: Leica confocal microscopy, 63x oil objective The original raw data and preliminary annotations were part of the following publication (please cite if you use the dataset): Long, F., Peng, H., Liu, X., Kim, S. K., & Myers, E. (2009). A 3D digital atlas of C. elegans and its application to single-cell analyses. Nature methods, 6(9), 667-672. The nuclei annotation masks were further manually curated by Dagmar Kainmueller (MDC Berlin) for the following publication: Hirsch, P., & Kainmueller, D. (2020). An auxiliary task for learning nuclei segmentation in 3d microscopy images. In Medical Imaging with Deep Learning (pp. 304-321). PMLR. We provide the dataset already structured into the train/validation/test split as used by the above as well as the following publications: Weigert, M., Schmidt, U., Haase, R., Sugawara, K., & Myers, G. (2020). Star-convex polyhedra for 3d object detection and segmentation in microscopy. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (pp. 3666-3673).