Fully automated 3D segmentation and separation of multiple cervical vertebrae in CT images using a 2D convolutional neural network.
Hyun-Jin BaeHeejung HyunYounghwa ByeonKeewon ShinYongwon ChoYoung Ji SongSeong YiSung-Uk KuhJin S. YeomNamkug KimPublished in: Comput. Methods Programs Biomed. (2020)
Keyphrases
- fully automated
- ct images
- fully automatic
- medical imaging
- liver segmentation
- x ray images
- medical images
- lung nodules
- fracture detection
- computed tomography
- convolutional neural network
- x ray
- ct scans
- ct data
- computer tomography
- manual segmentation
- pet ct
- semi automatic
- anatomical structures
- automated segmentation
- image analysis
- image segmentation
- region growing
- pet images
- treatment planning
- mr images
- medical image processing
- lung parenchyma
- magnetic resonance images
- magnetic resonance imaging
- registration process
- image registration
- segmentation algorithm
- completely automated
- pulmonary nodules
- microscopy images
- statistical shape model
- face detection
- imaging modalities
- patient specific
- clinical applications
- high resolution
- traumatic brain injury
- intraoperative
- ground glass opacity
- accurate segmentation