CHO cells nuclei virtual staining - BioImage.io

harshyadav1
Dec 31, 2015
1 min read

Author

Estibaliz Gómez de Mariscal, Mario Del Rosario

Description

A conditional cycleGAN trained to infer the cell membrane as seen in a widefield fluorescence image from phase contrast images of CHO cells imaged with phase contrast microscopy. The cells are imaged with a 20x objective.

Input channel: 2D images, grayscale
Bit depth: 32-bit float
Output channels: Cell membrane probability

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

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Download model file and test image (ZIP archive)

Requirements

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

Installation and apply instructions

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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/.