EDICNet: An end-to-end detection and interpretable malignancy classification network for pulmonary nodules in computed tomography.
Yannan LinLeihao WeiSimon X. HanDenise R. AberleWilliam HsuPublished in: Medical Imaging: Computer-Aided Diagnosis (2020)
Keyphrases
- end to end
- pulmonary nodules
- computed tomography
- ct images
- computer aided detection
- ct scans
- benign and malignant
- thoracic ct images
- computer aided diagnosis
- lung nodules
- text localization and recognition
- congestion control
- medical images
- medical imaging
- computer aided
- image reconstruction
- ct data
- lung cancer
- fracture detection
- three dimensional
- pattern recognition
- low dose
- x ray
- computer networks
- receiver operating characteristic
- breast cancer
- computer tomography
- machine learning
- cone beam ct
- image registration
- network traffic
- region of interest
- image processing
- x ray images