Postoperative glioma segmentation in CT image using deep feature fusion model guided by multi-sequence MRIs
In this study, the authors developed a deep feature fusion model (DFFM) in order to segment postoperative gliomas on CT images, which were guided by multi-sequence MRIs. The authors found that DFFM enabled accurate segmentation of CT postoperative gliomas, which may help to improve radiotherapy planning. Key points A fully automated deep learning method was developed to segment postoperative gliomas