help required for training dataset using unet
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I am trying to implement U-NET segmentation on 3Dircadb dataset.
The data set contains
i) Original LiverCT dataset
II) Masks of Liver CT dataset
lll) Labels of Liver CT dataset
my questios is
i) To train the unet algorithm what dataset i want to use
ii) How to identify labeled organ from label dataset
Even in the LITS dataset we have
i) original CT images
ii) maks of thr CT images
how to train unet using above dataset
am already using below options part in the training code
options = trainingOptions('sgdm', ...
'Momentum',0.5, ...
'InitialLearnRate',8e-4, ...
'L2Regularization',0.0005, ...
'MaxEpochs',50, ...
'MiniBatchSize',8, ...
'Shuffle','every-epoch', ...
'CheckpointPath', tempdir, ...
'VerboseFrequency',2, ...
'Plots','training-progress');
but am not able to segment the liver from original image so please help me if i want to update any extra information in the training part
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