Essential parameters needed for a U-Net-based segmentation of individual bones on planning CT images in the head & neck region using limited datasets for radiotherapy application.
Ama Katseena YawsonAlexander WalterNora WolfSebastian KlüterPhilipp HoegenSebastian AdebergJuergen DebusMartin FrankOliver JäkelKristina GiskePublished in: Physics in medicine and biology (2023)
With these insights, we are challenging the utilization of an automatic and accurate bone segmentation tool into the clinical routine of radiotherapy despite the limited training datasets.
Keyphrases
- deep learning
- convolutional neural network
- early stage
- locally advanced
- radiation therapy
- radiation induced
- rna seq
- machine learning
- computed tomography
- bone mineral density
- image quality
- clinical practice
- contrast enhanced
- rectal cancer
- squamous cell carcinoma
- high resolution
- dual energy
- positron emission tomography
- virtual reality
- magnetic resonance
- single cell
- bone loss
- optical coherence tomography
- postmenopausal women
- pet ct