Deep learning-based target tracking with X-ray images for radiotherapy: a narrative review.

ABSTRACT:

Background and objective

As one of the main treatment modalities, radiotherapy (RT) (also known as radiation therapy) plays an increasingly important role in the treatment of cancer. RT could benefit greatly from the accurate localization of the gross tumor volume and circumambient organs at risk (OARs). Modern linear accelerators (LINACs) are typically equipped with either gantry-mounted or room-mounted X-ray imaging systems, which provide possibilities for marker-less tracking with two-dimensional (2D) kV X-ray images. However, due to organ overlapping and poor soft tissue contrast, it is challenging to track the target directly and precisely with 2D kV X-ray images. With the flourishing development of deep learning in the field of image processing, it is possible to achieve real

SUBMITTER: Liu X 

PROVIDER: S-EPMC10963821 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature