Fully automatic deep learning-based lung parenchyma segmentation and boundary correction in thoracic CT scans.
Himanshu RikhariEsha Baidya KayalShuvadeep GangulyArchana SasiSwetambri SharmaD. S. DheekshaManish SainiKrithika RangarajanSameer BakhshiDevasenathipathy KandasamyAmit MehndirattaPublished in: Int. J. Comput. Assist. Radiol. Surg. (2024)
Keyphrases
- ct scans
- fully automatic
- deep learning
- ct images
- lung parenchyma
- liver segmentation
- computed tomography
- pulmonary nodules
- ct data
- automated segmentation
- medical images
- fully automated
- semi automatic
- x ray
- computer tomography
- medical imaging
- unsupervised learning
- region of interest
- lung nodules
- computer aided diagnosis
- abdominal organs
- machine learning
- low dose
- decision trees
- left ventricle
- image processing
- three dimensional
- pattern recognition
- image registration
- low contrast
- segmentation algorithm
- x ray images
- computer aided
- image reconstruction