Deep learning-based segmentation of the lung in MR-images acquired by a stack-of-spirals trajectory at ultra-short echo-times.
Andreas M. WengJulius F. HeidenreichCorona MetzSimon VeldhoenThorsten Alexander BleyTobias WechPublished in: BMC Medical Imaging (2021)
Keyphrases
- mr images
- accurate segmentation
- deep learning
- medical images
- magnetic resonance
- partial volume
- brain mr images
- magnetic resonance images
- brain tumors
- manual segmentation
- intensity inhomogeneity
- cardiac magnetic resonance
- segmentation result
- mr brain
- dice similarity coefficient
- unsupervised learning
- mr imaging
- image data
- ct images
- bias field
- automatic segmentation
- brain structures
- machine learning
- tissue segmentation
- contrast enhanced
- nonrigid registration
- mri data
- mental models
- computed tomography
- prostate cancer
- brain tissue
- weakly supervised
- deformable models
- segmentation algorithm
- anatomical structures
- segmentation method
- image segmentation
- ct scans
- semi supervised
- inter patient
- image processing