File size: 1,279 Bytes
7b650b1 e8e6847 652ec03 2f91a5a 652ec03 2f91a5a 3d0df08 2f91a5a 67f531b 2f91a5a 652ec03 2f91a5a 652ec03 2f91a5a 652ec03 67f531b 652ec03 596974f 652ec03 67f531b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 |
---
license: gpl-3.0
language:
- en
pipeline_tag: image-segmentation
---
# 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](https://github.com/stardist/stardist)
- [2] Stardist Paper : [ArXiv](https://arxiv.org/abs/1908.03636)
- [3] NuCount Training Dataset : [Zenodo](https://)
- [4] NuCount Github Project: [Github](https://github.com/andysaurin/3DL_NuCount/) |