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Official Data and Models

Datasets

We publicly release the datasets used for training the networks which available as part of the PlantSeg package. Please refer to our publication for more details about the datasets:

  • Arabidopsis thaliana ovules dataset (raw confocal images + ground truth labels)
  • Arabidopsis thaliana lateral root (raw light sheet images + ground truth labels)

Both datasets can be downloaded from our OSF project

Pre-trained Networks

The following pre-trained networks are provided with PlantSeg package out-of-the box and can be specified in the config file or chosen in the GUI.

  • generic_confocal_3D_unet - alias for confocal_3D_unet_ovules_ds2x see below
  • generic_light_sheet_3D_unet - alias for lightsheet_3D_unet_root_ds1x see below
  • confocal_3D_unet_ovules_ds1x - a variant of 3D U-Net trained on confocal images of Arabidopsis ovules on original resolution, voxel size: (0.235x0.075x0.075 µm^3) (ZYX) with BCEDiceLoss
  • confocal_3D_unet_ovules_ds2x - a variant of 3D U-Net trained on confocal images of Arabidopsis ovules on 1/2 resolution, voxel size: (0.235x0.150x0.150 µm^3) (ZYX) with BCEDiceLoss
  • confocal_3D_unet_ovules_ds3x - a variant of 3D U-Net trained on confocal images of Arabidopsis ovules on 1/3 resolution, voxel size: (0.235x0.225x0.225 µm^3) (ZYX) with BCEDiceLoss
  • confocal_2D_unet_ovules_ds2x - a variant of 2D U-Net trained on confocal images of Arabidopsis ovules. Training the 2D U-Net is done on the Z-slices (1/2 resolution, pixel size: 0.150x0.150 µm^3) with BCEDiceLoss
  • confocal_3D_unet_ovules_nuclei_ds1x - a variant of 3D U-Net trained on confocal images of Arabidopsis ovules nuclei stain on original resolution, voxel size: (0.35x0.1x0.1 µm^3) (ZYX) with BCEDiceLoss
  • lightsheet_3D_unet_root_ds1x - a variant of 3D U-Net trained on light-sheet images of Arabidopsis lateral root on original resolution, voxel size: (0.25x0.1625x0.1625 µm^3) (ZYX) with BCEDiceLoss
  • lightsheet_3D_unet_root_ds2x - a variant of 3D U-Net trained on light-sheet images of Arabidopsis lateral root on 1/2 resolution, voxel size: (0.25x0.325x0.325 µm^3) (ZYX) with BCEDiceLoss
  • lightsheet_3D_unet_root_ds3x - a variant of 3D U-Net trained on light-sheet images of Arabidopsis lateral root on 1/3 resolution, voxel size: (0.25x0.4875x0.4875 µm^3) (ZYX) with BCEDiceLoss
  • lightsheet_2D_unet_root_ds1x - a variant of 2D U-Net trained on light-sheet images of Arabidopsis lateral root. Training the 2D U-Net is done on the Z-slices (pixel size: 0.1625x0.1625 µm^3) with BCEDiceLoss
  • lightsheet_3D_unet_root_nuclei_ds1x - a variant of 3D U-Net trained on light-sheet images Arabidopsis lateral root nuclei on original resolution, voxel size: (0.25x0.1625x0.1625 µm^3) (ZYX) with BCEDiceLoss
  • lightsheet_2D_unet_root_nuclei_ds1x - a variant of 2D U-Net trained on light-sheet images Arabidopsis lateral root nuclei. Training the 2D U-Net is done on the Z-slices (pixel size: 0.1625x0.1625 µm^3) with BCEDiceLoss.
  • confocal_3D_unet_sa_meristem_cells - a variant of 3D U-Net trained on confocal images of shoot apical meristem dataset from: Jonsson, H., Willis, L., & Refahi, Y. (2017). Research data supporting Cell size and growth regulation in the Arabidopsis thaliana apical stem cell niche. https://doi.org/10.17863/CAM.7793. voxel size: (0.25x0.25x0.25 µm^3) (ZYX)
  • confocal_2D_unet_sa_meristem_cells - a variant of 2D U-Net trained on confocal images of shoot apical meristem dataset from: Jonsson, H., Willis, L., & Refahi, Y. (2017). Research data supporting Cell size and growth regulation in the Arabidopsis thaliana apical stem cell niche. https://doi.org/10.17863/CAM.7793. pixel size: (25x0.25 µm^3) (YX)
  • lightsheet_3D_unet_mouse_embryo_cells - A variant of 3D U-Net trained to predict the cell boundaries in live light-sheet images of ex-vivo developing mouse embryo. Voxel size: (0.2×0.2×1 µm^3) (XYZ)
  • confocal_3D_unet_mouse_embryo_nuclei - A variant of 3D U-Net trained to predict the cell boundaries in live light-sheet images of ex-vivo developing mouse embryo. Voxel size: (0.2×0.2×1 µm^3) (XYZ)

Selecting a given network name (either in the config file or GUI) will download the network into the ~/.plantseg_models directory. Detailed description of network training can be found in our paper.

The PlantSeg home directory can be configured with the PLANTSEG_HOME environment variable.

export PLANTSEG_HOME="/path/to/plantseg/home"