Cats or CAT scans: Transfer learning from natural or medical image source data sets?
V Cheplygina - Current Opinion in Biomedical Engineering, 2019 - Elsevier
Transfer learning is a widely used strategy in medical image analysis. Instead of only
training a network with a limited amount of data from the target task of interest, we can first
train the network with other, potentially larger source data sets, creating a more robust
model. The source data sets do not have to be related to the target task. For a classification
task in lung computed tomography (CT) images, we could use both head CT images and
images of cats as the source. While head CT images appear more similar to lung CT …
training a network with a limited amount of data from the target task of interest, we can first
train the network with other, potentially larger source data sets, creating a more robust
model. The source data sets do not have to be related to the target task. For a classification
task in lung computed tomography (CT) images, we could use both head CT images and
images of cats as the source. While head CT images appear more similar to lung CT …