How to start the training of a deep net from a given state?

I would like to start the training of a deep net from the state it was in after a previous training. In my application the user iteratively adds annotations and I want to avoid training the netwrok from scratch at each iteration. Here is the code I use to define and train the network:

layers = [ ... imageInputLayer([2*BoxRad+1 2*BoxRad+1 1]) convolution2dLayer([9 9],100,'Stride',1) reluLayer maxPooling2dLayer(2,'Stride',2) convolution2dLayer([5 5],25,'Stride',1) reluLayer maxPooling2dLayer(2,'Stride',2) fullyConnectedLayer(2) softmaxLayer classificationLayer]; options = trainingOptions('sgdm', 'MaxEpochs', 30, 'MiniBatchSize', 32); net = trainNetwork(Images,Lbl,layers,options);