FIGURE
Figure 1
- ID
- ZDB-FIG-220224-4
- Publication
- Wang et al., 2022 - A novel deep learning-based 3D cell segmentation framework for future image-based disease detection
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Figure 1
3DCellSeg: A two-stage light-weight, fast, and robust pipeline for 3D cell segmentation. [Note: There are two stages in the pipeline. The first stage is a semantic segmentation, where the input is a 3D cell membrane image and the output consists of three masks, which indicate whether a voxel is the cell foreground, membrane, or background. The second stage is an instance segmentation performed on the basis of these three masks. The cellular images and segmentation results were generated by Python Matplotlib ( |
Expression Data
Expression Detail
Antibody Labeling
Phenotype Data
Phenotype Detail
Acknowledgments
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