Deep-Learning-with-PyTorch

End-to-end
nodule analysis,
and where to go next
This chapter covers
• Connecting segmentation and classification
models
• Fine-tuning a network for a new task
• Adding histograms and other metric types to
TensorBoard
• Getting from overfitting to generalizing
Over the past several chapters, we have built a decent number of systems that are
important components of our project. We started loading our data, built and
improved classifiers for nodule candidates, trained segmentation models to find
those candidates, handled the support infrastructure needed to train and evaluate
those models, and started saving the results of our training to disk. Now it’s time to
unify the components we have into a cohesive whole, so that we may realize the full
goal of our project: it’s time to automatically detect cancer.
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