Shape constrained fully convolutional DenseNet with adversarial training for multiorgan segmentation on head and neck <scp>CT</scp> and low‐field <scp>MR</scp> images

Abstract

The performance of our previous shape constrained fully CNNs for H&N segmentation is further improved by incorporating GAN and DenseNet. With the novel segmentation method, we showed that the low-field MR images acquired on a MR-guided radiation radiotherapy system can support accurate and fully automated segmentation of both bony and soft tissue OARs for adaptive radiotherapy.