DeepGI

Gastrointestinal (GI) tract cancers require precise radiotherapy planning, and this paper introduces an automated approach to segment GI tract regions in MRI scans. The proposed model uses advanced deep learning architectures, including Inception-V4, UNet++ with a VGG19 encoder, and Edge UNet, to enhance segmentation accuracy and efficiency. This solution streamlines the traditionally manual segmentation process, offering a robust tool for clinicians in radiotherapy planning.