Registration free automatic contour adaptation using neural networks

A method comprising:

• receiving a current fraction image and a reference image each depicting an anatomy of a subject, the reference image corresponding to a previous radiotherapy treatment fraction, the current fraction image corresponding to a current radiotherapy treatment fraction;
• obtaining a reference segmentation associated with the reference image;
• encoding, by a current fraction encoder, the current fraction image to generate a first set of features;
• encoding, by a reference encoder, the reference image and the reference segmentation to generate a second set of features;
• decoding, by a decoder, a combination of the first set of features and the second set of features to generate a predicted segmentation of the current fraction image;
• and
• configuring a radiotherapy treatment parameter based on the predicted segmentation of the current fraction image.

A non-transitory computer readable medium comprising non-transitory computer readable instructions that, when executed by one or more processors, configure the one or more processors to perform operations comprising:

• receiving a current fraction image and a reference image each depicting an anatomy of a subject, the reference image corresponding to a previous radiotherapy treatment fraction, the current fraction image corresponding to a current radiotherapy treatment fraction;
• obtaining a reference segmentation associated with the reference image;
• encoding, by a current fraction encoder, the current fraction image to generate a first set of features;
• encoding, by a reference encoder, the reference image and the reference segmentation to generate a second set of features;
• decoding, by a decoder, a combination of the first set of features and the second set of features to generate a predicted segmentation of the current fraction image;
• and
• configuring a radiotherapy treatment parameter based on the predicted segmentation of the current fraction image.