Validation of automated lobe segmentation on paired inspiratory-expiratory chest CT in 8-14 year-old children with cystic fibrosis.
Philip KonietzkeOliver WeinheimerMark O WielpützDasha SavageTiglath ZiyehChristin TuBeverly NewmanCraig J GalbánMarcus A MallHans-Ulrich KauczorTerry E RobinsonPublished in: PloS one (2018)
Automatic lobe segmentation delivers excellent results for inspiratory and good results for expiratory CT. It may become an important component for lobe-based quantification of functional deficits in cystic fibrosis lung disease, reducing necessity for user-interaction in CT post-processing.
Keyphrases
- deep learning
- image quality
- dual energy
- computed tomography
- contrast enhanced
- cystic fibrosis
- convolutional neural network
- machine learning
- positron emission tomography
- magnetic resonance imaging
- mechanical ventilation
- pseudomonas aeruginosa
- traumatic brain injury
- high throughput
- chronic obstructive pulmonary disease
- air pollution