3DL_U-Net model

Model author: Mustapha EL AMMARI

Model description

The model has been designed by transfer tuning then fine tuning 3D U-Net model as autoencoder, using a home made dataset [1] composed of 3D image stack acquired using a confocal microscope. Training and Inference Notebooks are hosted on our Github repo [2].

Stardist Training parameters

patch size: (64,64,64)
batch size: 64
epochs : 200
image normalization: normalize channel independantly

Training dataset parameters

split : Train 0.8 / Val 0.2

Inference

patch size : (64,64,64)
model : file.h5

References

[1] Dataset Project: Zenodo
[4] 3D U-Net Github Project: Github