About
LACSS is a deep-learning model for single-cell segmentation from microscopy images.
References:
- https://www.nature.com/articles/s42003-023-04608-5
- https://arxiv.org/abs/2304.10671
Why LACSS?
LACSS is designed to utilize point labels for model training. You have three options:
| Method | Data(left) / Label(right) |
|---|---|
| Point |  |
| Point + Mask |  |
| Segmentation |  |
You can of course also combined these labels in any way you want.
What is included?
- A library for training LACSS model and performing inference
- A few pretrained models as transfer learning starting point
- SMC-based cell tracking utility for people interested in cell tracking
How to generate point label?
If your data include nuclei counter-stain, the easist way to generate point label for your image is to use a blob detection algorithm on the nuclei images:
Give it a try:
- Model training
- Supervised Training
- With point label + mask