Mouse Embryo Segmentation - BioImage.io

jose-miguelserra-l
Jan 1, 2016
2 min read

Authors

A. Wolny , V. Bondarenko

Description

A 3D U-Net trained to predict the nuclei and their boundaries in fixed confocal images of developing mouse embryo.

First model is for fixed embryos, second model for live embryos.

Input channel: 3D Stack, grayscale
Scale: (0.2 µm × 0.2 µm × 1 µm)
Bit depth: 8-bit or 16-bit
Output channel: Model 006 - Channel 0, probability of nuclei, Channel 1: probability of nuclei contour, Model 007 - probability of cell contours

This model was downloaded and converted from BioImage.io, respecting the associated license (see License section below for more information)

Download

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Model files (.zip)
Test images (.zip)

Download model files and test images (ZIP archive)

Requirements

Make sure you have installed Aivia and the required DeepLearning module (according to our Wiki).

Installation and apply instructions

Aivia is required for applying the model file. You can request a demo copy of Aivia here.

Drag-and-drop the model file into the Recipe Console area; or use the 'Load recipe' option in the Recipe Console to load the model file.
Load the test image (or any image of your own) into Aivia.
If your image contains more than one channel, click on the 'Input & Output' section and specify the image channel you wish to apply the model on.
Click 'Start' to apply the model.

License

Acknowledgement

Bioimage.io is supported by AI4Life. AI4Life has received funding from the European Union's Horizon Europe research and innovation program under grant agreement number 101057970.

About AI4Life: https://ai4life.eurobioimaging.eu/.