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pipeline for volumetric cell segmentation
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README.md

volumetric segmentation pipeline

Reference: https://doi.org/10.1016/j.cell.2019.05.050

Mu Y*, Bennett DV*, Rubinov M*, Narayan S, Yang CT, Tanimoto M, Mensh BD, Looger LL, Ahrens MB.

Glia accumulate evidence that actions are futile and suppress unsuccessful behavior.

Cell 2019 178:27-43.

dependencies

  • IPython 5.3.0

  • Apache Spark 1.6.2

  • Advanced Normalization Tools (ANTS) 2.1.0

installation

  • use pip to install: pip install git+https://github.com/mikarubi/voluseg.git

example usage

  • Download an example dataset folder:

    https://www.dropbox.com/sh/psrj9lusohj7epu/AAAbj8Jbb3o__pyKTTDxPvIKa?dl=0

  • Launch IPython with Spark.

  • Import package and load default parameters.

  • Set and save parameters (see voluseg.parameter_dictionary?? for details).

  • Execute code sequentially to perform cell detection.

  • The final output is in the file cells0_clean.hdf5 in the output directory.

example code

# set up
import os
import pprint
import voluseg

# check for updates
voluseg.update()

# set and save parameters
parameters0 = voluseg.parameter_dictionary()
parameters0['dir_ants'] = '/path/to/ants/bin/'
parameters0['dir_input'] = '/path/to/input/images/'
parameters0['dir_output'] = '/path/to/output/directory/'
parameters0['registration'] = 'translation'
parameters0['diam_cell'] = 5.0
parameters0['f_volume'] = 2.0
voluseg.step0_process_parameters(parameters0)

# load and print parameters
filename_parameters = os.path.join(parameters0['dir_output'], 'parameters.pickle')
parameters = voluseg.load_parameters(filename_parameters)
pprint.pprint(parameters)

print("process images.")
voluseg.step1_process_images(parameters)

print("align images.")
voluseg.step2_align_images(parameters)

print("mask images.")
voluseg.step3_mask_images(parameters)

print("detect cells.")
voluseg.step4_detect_cells(parameters)

print("clean cells.")
voluseg.step5_clean_cells(parameters)
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