3D Ground Truth Annotations of Nuclei in 3D Microscopy Volumes
Chen, A.; Wu, L.; Winfree, S.; Dunn, K. W.; Salama, P.; Delp, E. J.
Show abstract
In this paper we describe a set of 3D microscopy volumes we have partially manually annotated. We describe the volumes annotated and the tools and processes we use to annotate the volumes. In addition, we provide examples of annotated subvolumes. We also provide synthetically generated 3D microscopy volumes that can be used for training segmentation methods. The full set of annotations, synthetically generated volumes, and original volumes can be accessed as described in the paper.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- NISNet3D: Three-Dimensional Nuclear Synthesis and Instance Segmentation for Fluorescence Microscopy Images 97%
- Automated cell boundary and 3D nuclear segmentation of cells in suspension 94%
- UNI-EM: An Environment for Deep Neural Network-Based Automated Segmentation of Neuronal Electron Microscopic Images 94%
Similar papers in this journal
- FalseColor-Python: a rapid intensity-leveling and digital-staining package for fluorescence-based slide-free digital pathology 96%
- Mitochondrial event localiser (MEL) to quantitatively describe fission, fusion and depolarisation in the three-dimensional space 94%
- One-Shot phase-recovery using a Cellphone RGB Camera on a Jamin-Lebedeff Microscope 94%
Similar papers in this journal
- A Tailored Approach To Study Legionella Infection Using Lattice Light Sheet Microscope (LLSM) 94%
- Miniaturized widefield microscope for high speed voltage imaging 94%
- Hybrid machine-learning framework for volumetric segmentation and quantification of vacuoles in individual unlabeled yeast cells using holotomography 93%
Similar papers in this journal
Similar papers in this journal
- Setting up an institutional OMERO environment for bioimage data: perspectives from both facility staff and users 94%
- LiveLattice: Real-time visualization of tilted light-sheet microscopy data using a memory-efficient transformation algorithm 94%
- An Open-Hardware sample mounting solution for inverted light-sheet microscopes with large detection objective lenses 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.