Automated segmentation of an intensity calibration phantom in clinical CT images using a convolutional neural network.
Keisuke UemuraYoshito OtakeMasaki TakaoMazen SoufiAkihiro KawasakiNobuhiko SuganoYoshinobu SatoPublished in: Int. J. Comput. Assist. Radiol. Surg. (2021)
Keyphrases
- automated segmentation
- convolutional neural network
- ct images
- ct scans
- treatment planning
- clinical applications
- medical images
- computed tomography
- image intensity
- traumatic brain injury
- face detection
- medical imaging
- intensity information
- completely automated
- bone segmentation
- manual segmentation
- three dimensional
- segmentation method
- anatomical structures
- imaging modalities
- region of interest
- neural network
- magnetic resonance
- deformable models
- x ray
- pulmonary nodules
- fracture detection
- fully automated
- medical image analysis
- computer aided diagnosis
- medical data
- automatic segmentation
- computer vision
- computer assisted
- computer aided
- x ray images
- machine learning