Quantifying lung fissure integrity using a three-dimensional patch-based convolutional neural network on CT images for emphysema treatment planning.
Dallas K TadaPangyu TengKalyani VyapariAshley BanolaGeorge FosterEsteban DiazGrace Hyun J KimJonathan G GoldinFereidoun AbtinMichael F McNitt-GrayMatthew S BrownPublished in: Journal of medical imaging (Bellingham, Wash.) (2024)
A DL approach was developed to segment lung fissures on CT images and accurately quantify FIS. It has potential to assist in the identification of emphysema patients who would benefit from EBV treatment.
Keyphrases
- convolutional neural network
- deep learning
- image quality
- chronic obstructive pulmonary disease
- dual energy
- computed tomography
- contrast enhanced
- lung function
- epstein barr virus
- pulmonary fibrosis
- positron emission tomography
- idiopathic pulmonary fibrosis
- magnetic resonance imaging
- diffuse large b cell lymphoma
- magnetic resonance
- cystic fibrosis
- replacement therapy
- climate change
- pet ct