Feasibility evaluation of novel AI-based deep-learning contouring algorithm for radiotherapy.

Luis A Maduro BustosAbhirup SarkarLaura A DoyleKelly AndreouJodie NoonanDiana NurbagandovaSunJay A ShahOmoruyi Credit IraborFiras Mourtada

Published in: Journal of applied clinical medical physics (2023)

The highest agreement registered between OARs generated by Organs-RT and their respective references was for the bladder, heart, lungs, and femoral heads, with an overall DSC≥0.92. The poorest agreement was for the rectum, esophagus, and lips, with an overall DSC⩽0.81. Nonetheless, Organs-RT serves as a reliable auto-contouring tool by minimizing overall contouring time and increasing time-saving efficiency in radiotherapy treatment planning.

Keyphrases

deep learning
weight loss
early stage
artificial intelligence
locally advanced
radiation therapy
machine learning
radiation induced
spinal cord injury
heart failure
convolutional neural network
rectal cancer
atrial fibrillation
squamous cell carcinoma