Semi-supervised COVID-19 volumetric pulmonary lesion estimation on CT images using probabilistic active contour and CNN segmentation.
Diomar Enrique Rodriguez-ObregonAldo R. Mejía-RodríguezLeopoldo Cendejas-ZaragozaJuan Gutiérrez MejíaEdgar Roman Arce SantanaSonia Charleston-VillalobosTomás Aljama-CorralesAlejandro GabuttiAlejandro Santos-DíazPublished in: Biomed. Signal Process. Control. (2023)
Keyphrases
- ct images
- active contours
- lung parenchyma
- ct scans
- pet images
- level set
- semi supervised
- image segmentation
- shape prior
- medical images
- segmentation method
- cardiac ultrasound images
- computed tomography
- medical imaging
- region of interest
- energy functional
- energy function
- active contour model
- gradient vector flow
- snake model
- lung nodules
- object boundaries
- computer tomography
- fracture detection
- region growing
- curve evolution
- lymph nodes
- level set method
- chronic obstructive pulmonary disease
- lung cancer
- pulmonary nodules
- magnetic resonance images
- registration accuracy
- deformable models
- computer vision
- automatic segmentation
- segmentation algorithm
- image analysis
- anatomical structures
- ct data
- partial differential equations
- edge detection
- cardiac ct
- computer aided diagnosis
- range data
- image reconstruction
- x ray
- multi view
- multiscale
- image processing
- machine learning