Deep Learning for the Automatic Segmentation of Extracranial Venous Malformations of the Head and Neck from MR Images Using 3D U-Net.
Jeong Yeop RyuHyun Ki HongHyun Geun ChoJoon Seok LeeByeong Cheol YooMin Hyeok ChoiHo Yun ChungPublished in: Journal of clinical medicine (2022)
Our pilot study showed sufficient potential for the automatic segmentation of extracranial VMs through deep learning using MR images from VM patients. The overfitting phenomenon observed will be resolved with a larger number of MRI VM images.
Keyphrases
- deep learning
- convolutional neural network
- artificial intelligence
- contrast enhanced
- end stage renal disease
- machine learning
- internal carotid artery
- ejection fraction
- newly diagnosed
- chronic kidney disease
- magnetic resonance
- magnetic resonance imaging
- peritoneal dialysis
- prognostic factors
- computed tomography
- risk assessment
- patient reported outcomes
- optical coherence tomography