3DL_NuCount model
Model author: Fabrice Daian
Model description
3DL_NuCount model has been designed by fine tuning a pretrained Stardist3D model [1,2] using a home made dataset [3] in order to assess the number of cells present in a given 3D image stack acquired using an optical microscope. Training and Inference Notebooks are hosted on our Github repo [4].
Stardist Training parameters
- patch size: (48,96,96)
- batch size: 32
- epochs : 100
- data augmentation : flip/rotation/intensity
- image normalization: normalize channel independantly
- anisotropy: empirical
- rays : 96
Training dataset parameters
- tile size : (4,63,128,128)
- split : Train 0.8 / Val 0.2
Inference
- patch size : (784,784,:)
- image size : (2048,2048,:)
- model name : weights_best_1.h5
- config file : config.json
- threshold file : thresholds.json
References
- [1] Stardist Project: Github
- [2] Stardist Paper : ArXiv
- [3] NuCount Training Dataset : Zenodo
- [4] NuCount Github Project: Github
