Deep Learning-Based Air Trapping Quantification Using Paired Inspiratory-Expiratory Ultra-low Dose CT.
Sarah M. MullerSundaresh RamKatie J. BayfieldJulia H. ReuterSonja GestewitzLifeng YuMark Oliver WielpützHans-Ulrich KauczorClaus Peter HeusselTerry E. RobinsonBrian J. BartholmaiCharles R. HattPaul D. RobinsonCraig J. GalbánOliver WeinheimerPublished in: MICCAI (3) (2023)
Keyphrases
- deep learning
- low dose
- computed tomography
- x ray
- ct scans
- imaging modalities
- computer tomography
- lung nodules
- dual energy
- ct images
- unsupervised learning
- machine learning
- contrast enhancement
- medical images
- medical imaging
- three dimensional
- ct data
- weakly supervised
- x ray images
- image reconstruction
- mental models
- semi supervised