Semi-automated three-dimensional segmentation for cardiac CT images using deep learning and randomly distributed points.
Ted ShiMaysam ShahediKayla CaughlinJames D. DormerLing MaBaowei FeiPublished in: Medical Imaging: Image-Guided Procedures (2022)
Keyphrases
- randomly distributed
- ct images
- semi automated
- deep learning
- computed tomography
- medical images
- three dimensional
- medical imaging
- computer tomography
- lung nodules
- pet ct
- fracture detection
- fully automated
- ct scans
- unsupervised learning
- lung parenchyma
- x ray
- ct data
- machine learning
- image segmentation
- region of interest
- treatment planning
- segmentation algorithm
- clinical applications
- image analysis
- fully automatic
- imaging modalities
- cardiac ct
- mental models
- magnetic resonance images
- object segmentation
- level set
- deformable models
- data mining
- patient specific
- multiscale
- d objects
- multi view
- magnetic resonance
- magnetic resonance imaging
- image reconstruction
- vessel segmentation
- positron emission tomography
- accurate segmentation
- shape prior
- high dimensional
- ground glass opacity
- coronary artery