Methods and systems for radiotherapy treatment planning based on continuous deep learning
Abstract:
Example methods and systems for radiotherapy treatment planning based on continuous deep learning are provided. One example method may comprise: obtaining a deep learning engine that is trained to perform a radiotherapy treatment planning task based on first training data associated with a first planning rule. The method may also comprise: based on input data associated with a particular patient, performing the radiotherapy treatment planning task using the deep learning engine to generate output data associated with the particular patient; and obtaining modified output data that includes one or more modifications to the output data generated by the deep learning engine. The method may further comprise: based on the modified output data, generating second training data associated with a second planning rule; and generating a modified deep learning engine by re-training the deep learning engine using a combination of the first training data and the second training data.
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