Package: napari-segment-blobs-and-things-with-membranes
napari-segment-blobs-and-things-with-membranes (nsbatwm)This napari-plugin is based on scikit-image and allows segmenting nuclei and cells based on fluorescence microscopy images with high intensity in nuclei and/or membranes.UsageThis plugin populates image processing operations to theToolsmenu in napari.
You can recognize them with their suffix(nsbatwm)in brackets.
Furthermore, it can be used from thenapari-assistantgraphical user interface.
Therefore, just click the menuTools > Utilities > Assistant (na)or runnapariafrom the command line.You can also call these functions as shown inthe demo notebook.Voronoi-Otsu-LabelingThis algorithm usesOtsu's thresholding methodin combination withGaussian blurand aVoronoi-Tesselationapproach to label bright objects such as nuclei in an intensity image. The alogrithm has two sigma parameters which allow
you to fine-tune where objects should be cut (spot_sigma) and how smooth outlines should be (outline_sigma).
This implementation aims to be similar toVoronoi-Otsu-Labeling in clesperanto.Seeded WatershedStarting from an image showing high-intensity membranes and a seed-image where objects have been labeled (e.g. using Voronoi-Otsu-Labeling),
objects are labeled that are constrained by the membranes.Seeded Watershed with maskIf there is additionally a mask image available, one can use theSeeded Watershed with mask, to constraint the flooding
on a membrane image (1), starting from nuclei (2), limited by a mask image (3) to produce a cell segmentation within the mask (4).Seeded Watershed using local minima as starting pointsSimilar to the Seeded Watershed and Voronoi-Otsu-Labeling explained above, you can use this tool to segment an image
showing membranes without an additional image showing nuclei. The two sigma parameters allow to fine tune how close
objects can be and how precise their boundaries are detected.Gaussian blurApplies aGaussian blurto an
image. This might be useful for denoising, e.g. before applying the Threshold-Otsu method.Subtract backgroundSubtracts background usingscikit-image's rolling-ball algorithm.
This might be useful, for example to make intensity of membranes more similar in different regions of an image.Threshold OtsuBinarizes an image usingscikit-image's threshold Otsu algorithm, also known asOtsu's method.Split touching objects (formerly known as binary watershed).In case objects stick together after thresholding, this tool might help.
It aims to deliver similar results asImageJ's watershed implementation.Connected component labelingTakes a binary image and produces a label image with all separated objects labeled differently. Under the hood, it usesscikit-image's label function.Manual split and merge labelsSplit and merge labels in napari manually via theTools > Utilities menu:Thisnapariplugin was generated withCookiecutterusing with@napari'scookiecutter-napari-plugintemplate.InstallationThis plugin is part of devbio-napari. To install it, please follow itsinstallation instructions.ContributingContributions are very welcome. Tests can be run withtox, please ensure
the coverage at least stays the same before you submit a pull request.LicenseDistributed under the terms of theBSD-3license,
"napari-segment-blobs-and-things-with-membranes" is free and open source softwareIssuesIf you encounter any problems, please create a thread onimage.scalong with a detailed description and tag@haesleinhuepf.