AUTOMATED IMAGE SEGMENTATION SYSTEM AND METHOD

A method of training a learning network to perform image segmentation includes receiving training data from a trusted source and an alternative source; assigning weights to data in the second corpus; dividing the data into batches with samples from the first and second corpuses; and completing training epochs by, for each batch: generating an output for each sample; determining a loss by comparing the generated output with a ground truth for each sample; defining a discrepancy for each second corpus sample as a difference between the sample loss and the average loss for the first corpus, approximated as the average loss for the first corpus from the preceding epoch modified by a change in the average loss from the preceding to the current epoch; identifying weights for the next batch which minimise the weighted sum of discrepancies and network parameters which minimise the average weighted loss.