U-net for image segmentation

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Joseph Stember
Joseph Stember on 22 Aug 2017
Answered: Birju Patel on 9 Jun 2022
I was wondering if it is possible to download U-net (https://lmb.informatik.uni-freiburg.de/people/ronneber/u-net/) for use as a pretrained convolutional neural network for Matlab for medical image segmentation.
HARADHAN CHEL on 6 Mar 2020
In matlab documentation, it is clearly written how to build and train a U-net network when the input image and corresponding labelled images are stored into two different folders. But Surprisingly it is not described how to test an image for segmentation on the trained network. For testing images, which command we need to use? is it semanticseg? . Unfortunately this method is not working and not producing any result.

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Answers (3)

Moucheng Xu
Moucheng Xu on 16 Aug 2018
I think you can look at this one: https://www.mathworks.com/matlabcentral/answers/uploaded_files/107430/createUnet.m
This is a function I found online by mathworks for a modified version U net, I reproduced my own implementation of U net referring to this function so I could make other versions.
mohd akmal masud
mohd akmal masud on 12 Aug 2021
Edited: mohd akmal masud on 12 Aug 2021
Hi Moucheng Xu,
Is it this code can run in Matlab?

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Kris Fedorenko
Kris Fedorenko on 25 Aug 2017
Hi Joseph,
According to the documentation of u-net, you can download the ready trained network, the source code, the matlab binaries of the modified caffe network, all essential third party libraries and the matlab-interface for overlap-tile segmentation. Best bet would be to use the same setup as recommended by u-net, i.e. Ubuntu Linux 14.04 and Matlab 2014b (x64).
You might also find of interest the image segmentation functionality in the Image Processing Toolbox:
Hope this helps!
Ahmed on 7 Oct 2020
Hi Chris,
I want to apply UNet to segment weed plants, how can I label the images?

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Birju Patel
Birju Patel on 9 Jun 2022
The network you pointed to was trained in Caffe. You can use importCaffeNetwork to import this pretrained U-Net network:

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