Multi-organ auto-delineation in head-and-neck MRI for radiation therapy using regional convolutional neural network.

ABSTRACT: Magnetic resonance imaging (MRI) allows accurate and reliable organ delineation for many disease sites in radiation therapy because MRI is able to offer superb soft-tissue contrast. Manual organ-at-risk delineation is labor-intensive and time-consuming. This study aims to develop a deep-learning-based automated multi-organ segmentation method to release the labor and accelerate the treatment planning process for head-and-neck (HN) cancer radiotherapy. A novel regional convolutional neural network (R-CNN) architecture, namely, mask scoring R-CNN, has been developed in this study. In the proposed model, a deep attention feature pyramid network is used as a backbone to extract the coarse features given by MRI, followed by feature refinement using R-CNN. The final segmentation is obtained thro

SUBMITTER: Dai X 

PROVIDER: S-EPMC8811683 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature