  The job of Radiation oncologists is to deliver x-ray beams pointed toward the
tumor and at the same time avoid the stomach and intestines. With MR-Linacs
(magnetic resonance imaging and linear accelerator systems), oncologists can
visualize the position of the tumor and allow for precise dose according to
tumor cell presence which can vary from day to day. The current job of
outlining the position of the stomach and intestines to adjust the X-ray beams
direction for the dose delivery to the tumor while avoiding the organs. This is
a time-consuming and labor-intensive process that can easily prolong treatments
from 15 minutes to an hour a day unless deep learning methods can automate the
segmentation process. This paper discusses an automated segmentation process
using deep learning to make this process faster and allow more patients to get
effective treatment.
