Nuclei Segmentation (ilastik)

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Type
Workflow
Author
Paavolainen, Lassi
Requires
ilastik
scikit-image
SciPy
NumPy
Execution Platform
Linux
Mac
Windows
Implementation Type
plugin
Programming Language
Python
Supported image dimension
2D
Interaction Level
Automated
License/Openness
Free and open source
Description

NEUBIAS-WG5 workflow for nuclei segmentation using ilastik v1.3.2 and Python post-processing.

has function
Pixel classification
has topic
Machine learning
has biological terms
nucleus
nuclei
Additional keywords
probability map
Entry Curator
lascholz
Post date
03/15/2019 - 15:26
Last modified
04/25/2023 - 19:39
Workflow steps
Step 1: Get probability map with ilastik
ilastik
Pixel classification
Step 2: Threshold probability map to produce binary mask
scikit-image
Image thresholding
Step 3: Produce Euclidean distance map
scikit-image
Distance transform
Step 4: Find maxima
scikit-image
Image feature detection
Step 5: Watershed segmentation using the maxima as seed points
scikit-image
Watershed segmentation
Download Page
Neubias BIAFLOWS workflow of Nuclei Segmentation with Ilastik and Python
Reference Publication Link
Ilastik: Interactive learning and segmentation toolkit
has comparison
Neubias BIAFLOWS nuclei segmentation project