Cellular Segmentation

Provide CLI for cellular segmentation and visualization

Design mainly for quick visualization of results and batch processing (i.e., whole-brain image), and save as imageJ/Fiji .roi.

Supported packages

  1. Cellpose

  1. Stardist

If only small amount of images, the native GUI are recommended.

StarDist

Example of run an image segmentation in 2D mode and visualize using napari

python -m neuralib.segmentation.stardist.run_2d -F <IMAGE_FILE> --napari

  • It produces an output <IMAGE_FILE>.npz in the same directory, If the output exists, the napari will directly use the output. If need run again and rewrite the output, use --force-eval option

Example of run batch image segmentation in 2D mode from a directory (.tif files)

python -m neuralib.segmentation.stardist.run_2d -D <DIRECTORY> --suffix .tif

  • It produces multiple *.npz in the same directory.

See help using -h option

python -m neuralib.segmentation.stardist.run_2d -h

Cellpose

API Mode

Example of run an image segmentation in 2D mode and visualize using napari

python -m neuralib.segmentation.cellpose.run_api -F <IMAGE_FILE> --napari

  • It produces an output <IMAGE_FILE>_seg.npy in the same directory, If the output exists, the napari will directly use the output. If need run again and rewrite the output, use --force-eval option

Example of run an image segmentation in 2D mode and visualize using Cellpose GUI

python -m neuralib.segmentation.cellpose.run_api -F <IMAGE_FILE> --cpose

Example of run batch image segmentation in 2D mode from a directory (.tif files)

python -m neuralib.segmentation.cellpose.run_2d -D <DIRECTORY> --suffix .tif

  • It produces multiple *_seg.npy in the same directory.

See help using -h option

python -m neuralib.segmentation.cellpose.run_api -h

Subprocess Mode

Example of run an image segmentation in subprocess call

python -m neuralib.segmentation.cellpose.run_subproc -F <IMAGE_FILE>

  • It produces an output <IMAGE_FILE>_seg.npy in the same directory, If the output exists, the napari will directly use the output. If need run again and rewrite the output, use --force-eval option

Example of run batch image segmentation in subprocess call

python -m neuralib.segmentation.cellpose.run_subproc -D <DIRECTORY>

  • It produces multiple *.npy in the same directory.

See help using -h option

python -m neuralib.segmentation.cellpose.run_subproc -h